THE EFFECT OF MANAGEMENT OF WORKING CAPITAL
POLICIES ON FIRMS’ PROFITABILITY
Evidence from Manufacturing Private Limited Companies in
Tigray Region, Ethiopia
A Research Project Submitted To Mekelle University, Department Of
Accounting & Finance for the Award of the Degree of Master of Science in
Finance & Investment
By
Tewodros Abera Belay
Reg. No-- CBE/PR-031/01
Advisor:
Dr. FISSEHA GIRMAY, Ph.D.
Assistance professor of accounting & finance
Department of Accounting and Finance
College of Business & Economics
Mekelle University
Tigray – Ethiopia.
June, 2010
Mekelle, Ethiopia
A Study On
THE EFFECT OF MANAGEMENT OF WORKING
CAPITAL POLICIES ON FIRMS’ PROFITABILITY
Evidence from Manufacturing Private Limited Companies in Tigray
Region, Ethiopia
By
Tewodros Abera Belay
Reg. No-- CBE/PR-031/01
i
DEDICATION
In Memory Of My Brother Birhanu Gezahegn with Love!
You Are Always In My Thought!
ii
DECLARATION
I, Tewodros Abera, hereby declare that the Project work entitled “THE
EFFECT OF MANAGEMENT OF WORKING CAPITAL POLICIES ON
FIRMS’ PROFITABILITY: Evidence from Manufacturing Private Limited
Companies in Tigray Region, Ethiopia” submitted by me for the award of
the degree of Master of Science in Finance and investment of Mekelle
University at Mekelle, is original work and it has not been presented for
the award of any other Degree, Diploma, Fellowship or other similar titles
of any other university or institution.
Place: Mekelle
Signature:
Date: June, 2010
Name: Tewodros Abera
iii
CERTIFICATION
I certify that the project work entitled “THE EFFECT OF MANAGEMENT
OF WORKING CAPITAL POLICIES ON FIRMS’ PROFITABILITY:
Evidence from Manufacturing Private Limited Companies in Tigray
Region, Ethiopia” is a bona-fide work of Mr. Tewodros Abera who carried
out the research under my guidance. Certified further, that to the best of
my knowledge the work reported herein does not form part of any other
project report or dissertation on the bases of which a degree or award was
conferred on an earlier occasion on this or any other candidate.
Place: Mekelle
Signature:
Date: May, 2010
Dr. FISSEHA GIRMAY, Ph.D.
Assistance professor of accounting & finance
Department of Accounting and Finance
College of Business & Economics
Mekelle University
Tigray – Ethiopia.
iv
ACKNOWLEDGEMENTS
All praises to The God Almighty who has created this world of knowledge
for us. He is The Gracious, The Merciful. He bestowed man with
intellectual power and understanding, and gave him spiritual insight,
enabling him to discover his “Self” know his Creator through His wonders,
and conquer nature. Next to him, I thank his mother Saint Mary who is an
eternal torch of guidance and knowledge for whole mankind. She pray,
bless, protect and intercede for us sinners. AMEN!
Any achievement requires the effort of many people and this thesis is not
exceptional.
Thus,
many
individuals
have
been
supportive
and
instrumental in assisting me with this study; therefore, at least I owe them a
debt of gratitude and I have to tell other people about their help.
I am deeply thankful to my advisor, Dr. Fisseha Girmay (PhD), for his
persistent help in all the steps of the project, from title selection to writing
the final report, my debts are innumerable. His teaching methodology, do-it
attitude, continuous guidance, feedback, advice and encouragements have
been truly exceptional and learnable. Besides, his support, constructive
criticism, flexibility and kindness inspired me greatly and help me out to
complete my MSc program.
My heartfelt thanks also go to my friends Alemtsehay Jima, Bethlehem
Sisay, Tsion Taye and Rahawa Gebre who have opened their doors to
facilitate my work. I have learnt an enormous amount from them about
v
conducting research as well as thinking about new problems. Moreover,
they shared me their knowledge as well as material resources including
their office, computer and personal internet service. It would not be an
exaggeration to say that if they have not been there, I may not have reached
the finishing line.
In addition, it would not be justified if I do not mention the support of
Abebe Egigu (PhD Candidate), Hailemichael Tesfaye (MBA), Gurswamy D.
(PhD), Tesfay Aregawi (PhD Candidate), Jimawan R. (PhD) and Kasu
Mebratu (PhD Candidate). I thank you all for taking your precious time to
read my thesis and provide me with valuable comments.
Furthermore, this thesis would not have been possible without the support
of employees of ERCA, Mekelle branch who help me by giving me most of
the financial statements of the sample companies. I am especially indebted
to Hailemariam Etsana and all other employees ERCA Mekelle branch.
Finally, my warm thanks and love go to my wife, my mother, my brothers
and my sisters without whom I would not be the person I am today. My
work is the result of your perseverance, I love you all!
Tewodros Abera
May 2010
vi
ABSTRACT
Research studies on the effects of management of working capital policies on firms’ profitability
in developing countries, especially in Ethiopia remained an ignored area of empirical research.
Thus, this study examined the effect of working capital investment and financing policies on
firms’ profitability by using audited financial statements of a sample of 11 manufacturing private
limited companies in Tigray region, Ethiopia for the period of 2005 to 2009. The study used
return on assets, return on equity and operating profit margin as dependent profitability
variables. Accounts receivable period, inventory holding period and accounts payable period are
used as independent working capital investment policy variables. Moreover, cash conversion
cycle and current assets to total assets ratio are used as comprehensive measures of working
capital investment policy. On the other hand, current liabilities to total assets ratio is used as
measure of working capital financing policy. The two traditional measures, current ratio and
quick ratio, are used as liquidity indicators. In addition, the study used firm size as measured by
logarithm of sales, firm growth rate as measured by change in annual sales, financial leverage
and annual GDP growth rate as control variables. Both correlation analysis and pooled panel
data regression models of cross-sectional and time series data were used for analysis. The results
show that longer accounts receivable and inventory holding periods are associated with lower
profitability. There is also negative relationship between accounts payable period and profitability
measures; however, except for operating profit margin this relationship is not statistically
significant. The results also show that there exists significant negative relationship between cash
conversion cycle and profitability measures of the sampled firms. No significant relationship
between current assets to total assets ratio and profitability measures has been observed. On the
other hand, findings show that a highly significant positive relationship between current
liabilities to total assets ratio and profitability. Finally, negative relationships between liquidity
and profitability measures have also been observed. Managers, therefore, can increase firms’
profitability by improving the efficiency of management of working capital investment and
financing policies while, also keeping in view the trade-off between liquidity and profitability.
Keywords: Working capital investment and financing policies, Profitability, Liquidity
vii
TABLE OF CONTENTS
Title Page
Dedication
Declaration
CONTENTS
Pages
i
ii
iii
Certification
iv
Acknowledgements
Abstract
Table of Contents
Index of Tables & Figures
Acronyms
v
vii
viii
x
xi
CHAPTER I
INTRODUCTION
1.1. Background of the Study
1.2.Working Capital Management and the Researchers’
View
1.3 Statement of the Problem
1.4 Justification for the Study
CHAPTER II
CHAPTER III
1
1
3
3
4
1.5 Objectives of the Study
1.5.1 General Objective
1.5.2 Specific Objectives
1.6 Significance of the Study
1.7 Scope of the Study
1.8 Limitations of the Study
1.9 Chapterization
LITERATURE REVIEW
2.1 The Nature of Working Capital
2.2 Definition and Concept of Working Capital
2.3 Working Capital Management
2.4 Working Capital and Liquidity
2.5 Working Capital Policies
2.6 Significance of the Management of Working Capital
2.7 Effect of Working Capital Policies on Firms’
Profitability: Review of Previous Studies
2.8 Conceptual Framework for Analysis
METHODOLOGY
3.1 Research Design
5
5
5
5
6
7
7
8
8
9
11
13
14
17
19
3.2 Data Source and Collection Methods
36
viii
35
36
36
CHAPTER IV
CHAPTER V
REFERENCES
APPENDICES
3.3 Sampling Design
3.4 Data Analysis
3.5 Description of Variables and Research Hypotheses
3.5.1 Dependent Variables
3.5.2 Independent Variables and Respective
Research Hypotheses
3.5.3 Control Variables
3.7 Model Specifications
RESULTS AND DISCUSSION
4.1. Demographic Distribution of Sample Firms
4.2 Descriptive Statistics for the Study Variables
4.3 Correlation Analysis: Relationship between
Working Capital Policies and Firms’ Profitability
4.4. Econometrics Analysis: Effect of Working Capital
Policies on Firms’ Profitability
4.4.1 Accounts Receivable Period and Profitability
4.4.2 Inventory Holding Period and Profitability
4.4.3 Accounts Payable Period and Profitability
4.4.4. Cash Conversion Cycle and Profitability
4.4.5. Current Assets to Total Assets Ratio and
Profitability
4.4.6. Current Liabilities to Total Assets Ratio and
Profitability
4.5 Trade-Off between the Two Objectives of Working
Capital Management: Profitability and Liquidity
4.5.1. Current Ratio and Profitability
4.5.2. Quick Ratio and Profitability
CONCLUSION AND RECOMMENDATIONS
Appendix A: Sampling Frame of PLCs in Tigray
Appendix B: Balance Sheets & Income Statements
Appendix C: Checking Validity of OLS Assumptions
ix
36
38
39
39
40
44
44
48
48
48
52
60
61
63
66
70
73
76
79
79
81
85
91
97
INDEX OF TABLES & FIGURES
TABLE No.
Table 4.1
Table 4.2
Table 4.3
Table 4.4
Table 4.5
Table 4.6
Table 4.7
Table 4.8
Table 4.9
Table 4.10
Table 4.11
Table 4.12
Figure 1
DISCRIPTION
PAGE
Descriptive Statistics for the Study Variables
49
Correlation Analysis of Profitability with Accounts Receivable
53
Period and Control Variables
Correlation Analysis of Profitability Measures with Inventory
55
Holding Period, Accounts Payable Period, Cash Conversion
Cycle and Current Assets to Total Assets Ratio
Correlation Analysis of Profitability Measures with Current
58
Liabilities to Total Assets Ratio, Current Ratio, Quick Ratio and
GDP
Regression Analysis of Profitability Measures and Accounts
62
Receivable Period
Regression Analysis of Profitability Measures and Inventory
64
Holding Period
Regression Analysis of Profitability Measures and Accounts
67
Payable Period
Regression Analysis of Profitability Measures and Cash
71
Conversion Cycle
Regression Analysis of Profitability Measures and Current
74
Assets to Total Assets Ratio
Regression Analysis of Profitability Measures and Current
77
Liabilities to Total Assets Ratio
Regression Analysis of Profitability Measures and Current
80
Ratio
Regression Analysis of Profitability Measures and Quick Ratio
82
Conceptual Framework for Analysis
35
x
ACRONYMS
APP
ARP
CATAR
CCC
CLTAR
CR
GDP
ERCA
FGR
FL
FS
IHP
OLS
OPM
QR
ROA
ROE
Accounts Payable Period
Accounts Receivable Period
Current Assets to Total Assets Ratio
Cash Conversion Cycle
Current Liabilities to Total Assets Ratio
Current Ratio
Gross Domestic Product
Ethiopian Revenue and Customs Authority
Firm Growth Rate
Financial Leverage
Firm Size
Inventory Holding Period
Ordinary Least Squares
Operating Profit Margin
Quick Ratio
Return on Assets
Return on Equity
xi
CHAPTER I
INTRODUCTION
1.1 Background of the Study
Corporate Finance decisions are generally divided into two main parts: the management
of assets (investments decisions) and source of funds or liabilities and equity (financing
decisions), in the long-term and the short-term (Pandey, 2007; Ross, et al., 2000). The
management of short-term assets and related liabilities is called working capital
management. Working capital is the capital available for conducting the day-to-day
operations of an organization; it represents firms’ investment in short term assets.
Working capital policies of a firm are concerned with two decision areas. Determination
of appropriate level of investment in current assets and mix of current assets and
decisions as to what methods of financing to use to obtain funds for this investment.
They are parts of investment and financing decisions respectively.
Although there is no standard fixed requirement, all businesses, to one degree or
another, require working capital. The actual amount required will depend on many
factors such as the age of the company, the type of business activity, credit policy,
market and demand conditions, technology and manufacturing policy, operating
efficiency, availability of credit from suppliers and price level changes (Pandey, 2007). It
is indispensable that an appropriate amount of working capital is budgeted to meet
anticipated future needs. Failure to budget correctly could result in the business being
unable to meet its liabilities as they fall due. If a business finds itself in such a situation,
it is said to be technically insolvent. In conditions of uncertainty, firms must hold some
minimal level of cash and inventories based on expected sales plus additional safety
stocks.
1
The management of working capital is very important to businesses of all sizes
(Padachi, 2006). First, it consists of a large portion of firms’ investment. It represents
around 40 percent of total assets in a typical manufacturing firm and 50 percent to 60
percent of total assets in retailing and wholesales (Moyer, et al., 1995; Sebhatleab, 2002).
Second, according to Smith (1980), the efficient management of working capital is
important from the point of view of liquidity (risk) and profitability as well as firm
value. Poor management of working capital results in unnecessary investment in
unproductive assets or inadequate investment in current assets. Unnecessary investment
in current assets will tie up funds idle and hence reduces firms’ ability to invest in
productive assets such as plant and machinery, thereby reducing profitability. On the
other hand, inadequate investment in current assets reduces the liquidity position
causing insolvency, which intern leads to bankruptcy.
In history, working capital management has evolved through different stages, mainly–
the control, optimization and value creation (Sebhatleab, 2002). Initially, it was started as
an organized way of controlling current assets like balances of cash, receivables and
inventories. At this stage the main objective was to make sure that working capital is not
embezzled. At that time both researchers and practitioners, therefore, were developed
various control procedures. During the optimization phase, the main focus was not only
on the physical safety of working capital items but also on the optimization of
accounting profits by minimizing related costs and maximizing related income. At this
stage particular models like cash optimization models and inventory optimization
models were developed to ensure that firms do not get problems due to lack of liquidity
or incur too many costs by holding excessive working capital levels. The last stage, the
value creation stage, concentrated on how to help managers in the creation of value
without disregarding the above two objectives. Particularly, the cash flows approach is
has used as a main tool to measure the value created by firms. In this research, the
researcher used the cash conversion cycle as a measure of continuous cash or liquidity
flow to analyze the effect of working capital policies on firms’ profitability.
2
1.2 Working Capital Management and the Researchers’ View
While working capital assets and the related short-term liabilities affects firms’
profitability and liquidity (risk) as well as market values of shares (Smith, 1980),
habitually the corporate finance literature have focused on the study of long-term
financial decisions such as long-term investments, capital structure, dividends or
company valuation decisions, among other topics. To put it simply, many finance
scholars does not view working capital management as important research topic that
requires empirical investigation (Afza and Nazir, 2007).
According to Lamberson
(1995), however, working capital management has become one of the most important
issues in the organizations where many financial executives are struggling to identify
the basic working capital determinants and the appropriate level of working capital. In
other words, in practice firms try to keep an optimal level of working capital that
maximizes their profitability as well as value (Deloof, 2003).
Working capital
management of a business covers all the company’s activities relating to vendor,
customer and product (Sebhatleab, 2002). Then it requires a “Total” approach that
considers such activities. This means that firms should have to manage efficiently both
internal and external aspects of working capital (Hall, 2002; Sebhatleab, 2002). It
requires, therefore, the focus of researchers’ in identifying its determinants and
examining its effect on firms’ performance as well as risks. Consequently, companies
can minimize risk and improve the overall performance by understanding the role and
drivers of working capital from the studies.
1.3 Statement of the Problem
The effect of working capital management on corporate profitability has been studied
substantially by different researchers (Deloof, 2003; Filbeck and Krueger, 2005; Lazaridis
and Tryfonidis, 2006; Padachi, 2006; Samiloglu and Demirgunes, 2008; Shin and Soenen,
1998). Most of these and other researchers identify significant relationship between
efficiency in working capital management and firms’ performance. However, almost all,
3
these studies concentrated on large firms operating within well developed money and
capital markets of developed economies. From such findings it is difficult to generalize
for relatively small size Ethiopian firms that operate within an undeveloped financial
sector (with limited financial markets), where firms mostly obtain funds for their needed
investment in working capital from owner financing, trade credit and short term bank
loans. Research studies on the effects of management of working capital policies on
firms’ profitability in developing countries, especially in Ethiopia remained an ignored
area of empirical research. To the best of researcher’s knowledge, no research has been
done in Ethiopia in general, in Tigray in particular. Thus with this serious shortcomings
of the current literature, this study contributes to the existing literature by studying the
issue at hand specifically for Tigray region, Ethiopia. Generally, the researcher
conducted this study with the aim of providing answers to the following basic research
questions:
1. Does working capital investment policy affect profitability of Private Limited
Companies in Tigray?
2. Does working capital financing policy affect profitability of Private Limited
Companies in Tigray?
3. How are profitability and liquidity related in Tigray Private Limited Companies?
1.4 Justification for the Study
Working capital may be regarded as the life blood of business. Working capital is of
major importance to internal and external analysis because of its close relationship with
the current day-to-day operations of a business. It is common knowledge that a firm's
value cannot be maximized in the long run unless it survives the short run. Firms fail
most often because they are unable to meet their working capital needs; consequently,
sound working capital management is a requisite for firm survival. About 60 percent of
a financial manager's time is devoted to working capital management and many of the
4
potential employees in finance-related fields will find out that their first assignment on
the job will involve working capital (Afza and Nazir, 2007; Sebhatleab, 2002). However,
as explained above finance literature gives no or very little focus for the management of
working capital (Afza and Nazir, 2007). For these reasons, management of working
capital policy specially its effect on firms’ profitability is an essential topic of study.
1.5 Objectives of the Study
1.5.5 General Objective
The general objective of this study is to investigate the effect of working capital
investment and financing polices on profitability of manufacturing private limited
companies in Tigray, Ethiopia. Whilst, also look into the relationship between the two
goals of working capital management policies: liquidity and profitability.
1.5.2 Specific Objectives
The specific objectives of this study are:1. To examine the effect of working capital investment policy on firms’ profitability.
2. To investigate the effect of working capital financing policy on firms’
profitability.
3. To examine the relationship between the two objectives of working capital
policies: liquidity and profitability.
1.6 Significance of the Study
The study is significant at least for the following two reasons. First, as it has been
discussed in the problem statement part, no empirical research has been done yet to
examine the effect of working capital management on firms’ profitability in Tigray.
Hence, the findings of this study have a great contribution to the body of knowledge by
identifying how working capital management efficiency will affect the profitability of
5
manufacturing private limited companies in Tigray. Second, it can serve as a good base
for the forthcoming researchers who want to do a further research on this topic in Tigray
region, Ethiopia or else where. Thus, by developing a conceptual framework regarding
the relationship between working capital management and profitability of companies, in
this research presented hereafter, the researcher contributes to the current literature.
Generally, stakeholders such as researchers, policy makers, professionals and managers
can use the research to guide future research, reappraise current business practices, and
provide basic guidelines for new working capital policies in a dynamic business
environment.
1.7 Scope of the Study
In a nut shell, this research study is delimited to:
Topic: the topic of this study is delimited to examining the effects of management of
working capital investment and financing policies on firms’ profitability whilst, also
look into the relationship between profitability and liquidity.
Variables Used: the variables used are delimited to the four types of variablesprofitability, working capital policies, liquidity and control variables, that are described
in chapter three.
Study area: The geographical scope of this study is delimited in to the boundary of
Tigray Regional State, Ethiopia.
Sampling Units and size of sample: the sampling units of this study are delimited to 80
manufacturing private limited companies located and operating in Tigray and the
sample size is delimited to 11companies.
Methodology used: the methodology is delimited only to quantitative method with
descriptive statistics, correlation and econometrics analysis tools.
6
1.8 Limitations of the Study
The sample size for this study may no be large enough to study the issue and to
represent the study population, for the very reason that, there are limited number of
firms with an operating life of more than five years and also the problem of getting
complete financial information for the study period. Moreover, primary data was not
used due to time and financial constraints. These may limit the findings of the research.
1.9 Chapterization
This thesis consists of five chapters, including the first introductory chapter just
discussed. The second chapter discusses the theoretical underpinnings and the works of
previous researchers from which the conceptual framework for analysis and the
hypotheses are derived. The research methodology with the description of variables and
hypotheses of the study is presented in the third chapter. In the fourth chapter, the
results and discussions of empirical data collected and analyzed using descriptive
statistics, correlation analysis and econometrics models are presented. In the final
chapter, summary of findings of the study, conclusion and possible recommendations
are provided.
7
CHAPTER II
LITERATURE REVIEW
2.1. The Nature of Working Capital
While assets represent wealth of the firm, firms may not want to hold many of the assets
appearing on the balance sheet (Bhattacharyya, 1987; Sebhatleab, 2002). In a perfect
world, the production process takes very little time to convert the raw materials to
finished products which gets sold immediately in cash when it completed the
production process; and the input market is so perfect that any amount of raw material
is available at any time at a fixed price. There is no uncertainty, no transaction costs, and
no scheduling costs of production or constraints of technology. The unit costs of
producing goods will not change with the amount produced. Firms can borrow and
lend at the same interest rate. Capital, labor and product markets are perfectly
competitive and reflect all available information. In such an ideal world firms may like
to hold fixed assets like plant and machinery which produce goods and services; the
sales of which generate a profit; current assets like accounts receivable, inventories or
even cash are not likely to be held in the business.
However, this is an ideal situation difficult to have in the real world. Instead, the
production process takes quite some time; the finished products are not sold so quickly
which means a quantity of stocks remains in the warehouse. Moreover, the sales are not
always in cash; some amount of credit has to be given and the input markets are so
uncertain, so that, firms have to keep a certain amount of safety stock all the time. These
‘non-ideal’ conditions thus generate certain assets which are called current assets and
the levels of these assets make a significant part of a firm’s investment in its total assets.
Current assets, therefore, block the funds which should have been otherwise available
for meeting working expenses. Each and every current asset of a firm is, thus, nothing
but congealed fund for working expenses. And because business is a continuous
8
process, every cycle of operation generates these current assets which need to be funded
for immediate financing of working expenses. This funding for working expenses is
done by, what we popularly call, working capital.
2.2. Definition and Concept of Working Capital
The term working capital originated with the old Yankee peddler, who would load up
his wagon with goods and then go off on his route to peddle his wares (Brigham and
Gapenski, 1996). The merchandise was called working capital because it was what he
actually sold, or turned over, to produce the profits. The wagon and horse were the
fixed assets. The peddler generally owned the horse and wagon so, they are financed
with equity capital. But, he borrowed the funds to buy the merchandise. These
borrowing were called working capital loan, they had to be repaid after each trip to
demonstrate to the bank that the credit was sound. If the peddler was able to repay the
loan, then the bank would make another loan, and banks that followed this procedure
were said to be employing sound banking practices.
The concept of working capital was, perhaps, first evolved by Marx (1867), thought in a
somewhat different form. Marx used the term ‘variable capital’ meaning outlays for
payrolls advanced to workers before the goods they worked on were complete. He
contrasted this with ‘constant capital’, which according to him, is nothing but ‘dead
labor’, i.e. outlays for raw materials and other instruments of production produced by
labor in earlier stages which are now needed live labor to work with in the present
stage. This ‘variable capital’ was the wage fund which remains blocked in terms of
financial management, in work-in-process along with other operating expenses until it is
released through sale of finished goods. Although Marx did not mention that workers
also gave credit to the firm by accepting periodical payment of wages which funded a
portion of work-in-process, the concept of working capital, as we understand today, was
embedded in his ‘variable capital’.
9
The working capital of a business enterprise can be said as portion of its total financial
resources which is put to a variable operative purpose (Brigham and Gapenski, 1996).
The facilities that are necessary to carry on the productive activity and represented by
fixed assets investment (i.e. non- current asset investment) are to be operated by
working capital. In an annual survey of industries by government of India (2008), the
working capital is defined as "stocks of raw materials, stores, fuels, semi finished goods,
including work in progress and finished products; cash in hand and at the bank and the
algebraic sum of sundry creditors as represented by (a) outstanding factor payments e.g.
rent, wages, interest and dividends; (b) purchase of goods and services; (c) short term
loan and advances and sundry debtors comprising amounts due to the factory on the
account of sale of goods and services and advances towards tax payments."
But with the evolution of the concept came there were controversy about the definition
of working capital. Guthman and Dougall (1948) defined working capital as excess of
current asses over current liabilities. This view was elaborated by Gladson (1951) when
he defined working capital as the excess of current assets of a business (cash, accounts
receivables, inventories, for example) over current items owed to employees and others
(such as salaries and wages payables, accounts payables, taxes owed to government).
This concept of working capital, as has been commonly understood by the accountants,
more particularly understood as net working capital to distinguish it from gross
working capital which represents total current assets (Sen and Oruc, 2009). Walker
(1964) holds that this concept is useful to groups interested in determining the amount
and nature of assets that may be used to pay current liabilities. These interested groups,
as suggested by Walker, mostly composed of creditors, particularly the supply creditors
who may be concerned to know the ‘margin of safety’ available to them when the
realization of current assets be delayed for some reasons.
10
2.3 Working Capital Management
The term capital is used in deferent ways in economics and in finance (Bhattacharyya,
1987). In economics, the term capital represents goods consisting of a great variety of
things, namely, machines of various kinds, plants, houses, tools, raw materials and
goods-in-process. A finance manager of a firm looks for these things on the assets side of
the balance sheet. For capital, he turns his attention to the other side of the balance sheet
and never commits the mistake of adding the two together while taking the census of
total capital of the business. Although economists regard fixes capital as what is
represented by long-term assets, a finance manager defines fixed capital as that having
long term maturity.
It is not necessary to restrict utilization of the fixed capital to finance fixed asset only;
rather, to use the fixed capital to finance a part of current assets also in addition to
financing fixed assets is preferred. There may also be a situation where all the fixed and
current assets are financed from fixed capital only. In the latter case, the firm will have
current assets but no current liability, but we cannot say that the firm does not have any
need for working capital. The firm might not desire to contract current liability, but its
operations would have generated current assets which have to be funded to ensure
continuity of production. This fund is, in fact, an additional fund over and above the
fund required to meet working expenses of the firm.
Working capital management refers to all those decisions and activities a firm
undertakes in order to manage efficiently the elements of current assets (Brigham and
Gapenski, 1996; Pandey, 2007). Van-Horne and Vachowicz (2004) defined the working
capital management as that aspect of financial activity that is concerned with the
"safeguarding and controlling of the firm's current assets and the planning for sufficient
funds to pay current bills." Management of current assets is, therefore, distinct from the
management of fixed assets. But more important than this tautology is that because of
the dynamism of the current assets, the finance manager has to be constantly on guard
11
to ensure that their dynamic stability is not impaired to affect the net worth of the firm
negatively. Gross current assets should, therefore, be understood by their own meaning,
connotation and effect on the firms and should not mechanically equated with gross
working capital just because arithmetically the two may appear to be same in a balance
sheet. Besides, the funding operations of the current assets are quite distinct from the
management of current assets. A modern day finance manager first projects the level of
current assets of the firm under projected sales and then tries to find out sources to
finance these current assets in such a way that cost of capital is optimized.
Management of gross current assets and gross working capital, or simply working
capital, is not one and the same. The total of projected current assets is an aggregate
figure for which capital has to be raised and the two may not have any bearing on each
other. The profiles of the types of capital so raised in regard to the risk opportunity for
gain or loss and also the cost are different from that of current assets.
Working capital is so much in use in common parlance and is so much misunderstood.
Even among the professional managers the controversy and confusion persist. While an
accountant will regard working capital as current assets minus current liabilities and
call it as net working capital, a finance manager will consider gross current assets as the
working capital. Both may be true, but their concerns differ. The former’s concern is
arithmetical accuracy trained as he is to tally the two sides of the balance sheet. But the
finance manager’s concern is to find fund for each item of current assets at such costs
and risks that the evolving financial structure remains balanced between the two.
When one asks a production controller: what is working capital? His answer is very
simple and straightforward that working capital is the fund needed to meet the day-today working expenses, i.e. to pay for materials, wages and other operating expenses. Is
there any difference between the statements of ultimate analysis; the latter may be true,
but according to the accountant or the finance manager it is the very working expenses
that get blocked in current assets along the productive-distributive line of an enterprise,
12
and net working capitals that liquidity which takes care of the working expenses if the
line gets extended due to any reason.
2.4 Working Capital and Liquidity
According to Moyer, et al., (1998), the dual goals of working capital management are
liquidity and profitability. Managing liquidity, costs related to excesses and shortages of
working capital, can increase firms’ profitability.
Firms have to determine the
individual and joint impact of the levels of short-term investment and financing on the
dual objectives of working capital management. These goals imply that decisions that
tend to maximize profitability tend to minimize liquidity and vice versa. Conversely,
focusing almost entirely on liquidity will tend to reduce the potential profitability of the
firm (Brigham and Gapenski, 1996; Eljelly, 2004; Ross, et al., 2000).
However, the notion of the liquidity itself has undergone considerable changes with the
advances in financial management during the recent years. Liquidity has so far been
defined as a pyramid of current assets in descending order of realisability with cash
holding the top position and inventory, the last. This notion has given rise to liquidity
ratios such as current ratio or quick ratio, and later to the concept of net working capital.
The pyramid is no upside down with inventory at the top. When we examine the
pipeline theory of working capital, we will find that pipeline of the productivedistributive system of an enterprise consists of only inventories which, at different
stages, take on different names like work-in-progress, finished goods, accounts
receivable, cash balance, etc. Working capital structure is being so designed today in
efficient organizations as to take care of this fundamental liquidity of an enterprise with
zero or even negative net working capital.
Firms may have an optimal level of working capital that maximizes their value. Large
inventory and a generous trade credit policy may lead to high sales. Larger inventory
reduce the risk of the stock-out and trade credit may stimulate sales because it allows
customers to assess product quality before paying (Deloof and Gegers, 1996; Long, et al.,
13
1993). Because suppliers my have significant cost advantages over financial institutions
in providing credit to there customers, it can also be an inexpensive source of credit for
customer (Peterson and Rajan, 1997). The flip side of granting trade credit and keeping
inventories is that money is locked up in working capital.
2.5 Working Capital Policies
Working capital policies refer to decisions relating to the level of current assets and the
way they are financed (Ross, et al., 2000). These policies have been divided into two
categories by Weinraub and Visscher (1998). A firm may adopt an aggressive working
capital investment (asset management) policy with a low level of current assets as
percentage of total assets. On the other hand, aggressive working capital financing
policy uses high level of current liabilities as percentage of total liabilities. Excessive
levels of current assets may have a negative effect on the firm’s profitability whereas a
low level of current assets may lead to lower level of liquidity and stock-outs resulting
in difficulties in maintaining smooth operations (Van-Horne and Wachowicz, 2004).
Moreover, aggressive working capital financing policy that utilize higher levels of
normally lower cost short-term debt increase the risk of a short-term liquidity problem.
Therefore, more aggressive working capital policies are associated with higher return
and higher risk while conservative working capital policies are concerned with the
lower risk and return (Carpenter and Johnson, 1983; Gardner, et al., 1986; Weinraub and
Visscher, 1998). The main objective of working capital management is to maintain an
optimal balance between each of the working capital components. Business success
heavily depends on the ability of financial executives to effectively manage receivables,
inventory, and payables (Filbeck and Krueger, 2005). Firms can reduce their financing
costs and/or increase the funds available for expansion projects by minimizing the
amount of investment tied up in current assets. Most of the financial managers’ time and
effort are allocated in bringing non-optimal levels of current assets and liabilities back
toward optimal levels (Lamberson, 1995).
14
An optimal level of working capital would be the one in which a balance is achieved
between risk and efficiency. It requires continuous monitoring to maintain proper level
in various components of working capital i.e. cash receivables, inventory and payables
etc. The optimal level of working capital is determined to a large extent by the methods
adopted for the management of current assets and liabilities. It requires incessant
management to maintain proper level in various components of working capital i.e.
cash, receivables, inventory and payables etc. In general, current assets represent
important component of total assets of a firm.
A firm may be able to reduce the investment in fixed assets by renting or leasing plant
and machinery, whereas, the same policy cannot be followed for the components of
working capital. The high level of current assets may reduce the risk of liquidity
associated with the opportunity cost of funds that may have been invested in long-term
assets. The impact of working capital policies is highly important. These profitability
assumptions suggest maintaining a low level of current assets and a high proportion of
Current liabilities to total liabilities. This strategy will result in a low, or conceivably
negative, level of a working capital. Offsetting the profitability of this strategy, however,
is the increased risk to the firm. In determining the appropriate amount, or, level, of
current assets, management must consider the trade- off between profitability and risk.
Many surveys have indicated that managers spend considerable time on day-to-day
problems that involve working capital decisions. One reason for this is that current
assets are short-lived investment that are continually being converted into other assets
types (Rao, 1989). For example, cash is used to purchase inventory items eventually
become accounts receivable when they are sold on credit; and finally, the receivable are
transformed into cash when they are collected. With regard to current liabilities, the firm
is responsible for paying these obligations on a timely basis. The ability to match short
term obligations has only improved from a liquidation perspective and not from a going
concern approach (Shulman and Dambolena, 1986). A firm’s net working capital is also
15
often used as a measure of its liquidity position. That is, it represents the risk or
probability that a firm will be unable to meet is financial obligations as they come due.
Therefore, the more net working capital a firm has, the greater its ability to satisfy
credits demands. Moreover, because net working capital serves as liquidity risks
measure the firm’ net working capital position will affect its ability to acquire debt
financing. For example, commercial banks often impose minimum working capital
constraint in their loan agreements with firms similarly; bond indentures may contain
such restrictions. Due to the credit squeeze, the problem of working capital management
has acquired special importance. The shift in the emphasis from security to purpose of
advance has affected a large number of borrowers. Beside this, norms for inventory and
debtors have also been laid down. To aim at a sense of discipline in the working capital
management all these developments have been introduce.
The level and nature of firms’ investment depend on the firms’ product types, its
operating expenses, and management policy. As sales increase over time, more cash,
receivable, and inventories usually are needed. Even within a firm’s normal operating
cycle, seasonal sales patterns cause the level of current assets to be relatively high or low
at any particular point. Moreover, the firms’ credit and inventory policies, and how
efficiently it manages its current assets, can drastically affect a firms working capital
need. For example, a conservative manufacturer may maintain a high level of inventory
to satisfy unexpected demands or to hedge against delays in acquiring new inventory.
On the other hand, a more aggressive manufacturer may function with a much lower
investment in inventories. Current assets provide the liquidity necessary to support the
realization of the expected returns from firms’ long-term investments. The cash flows
associated with long-term investments are uncertain and irregular, and it is the non
synchronous nature of the cash flows that makes working capital necessary. Otherwise,
a mismatch between cash inflows and outflows could a liquidity crisis. This, in turn,
could disrupt or reduce the long-term returns expected from a firm's fixed asset
investment. Current assets therefore act as a buffer to reduce the mismatch between
16
cash outflows for goods and services and the cash receipts generated by the sales
revenues.
2.6 Significance of the Management of Working Capital
A research by Lamberson (1989) provided an insight into the importance and utilization
of financial analysis and working capital management by small manufacturers in U.S.A
questionnaire was mailed to chief financial officers of 477 small firms in the southern
region of U.S. The 85 percent of the respondents indicated that they use ratio analysis
for financial planning on monthly basis. Working capital management was ranked
important and most important by 90 percent of the respondents. The importance of
working capital management for small firms was, perhaps, due to their limited access to
capital markets and finance providers. Accounts receivables and inventory management
among the various components of working capital were ranked the most important
while cash management was ranked least important by small manufacturers.
For the success of an enterprise proper management of working capital is very
important. In finance literature there is a common opinion about the importance of
working capital management. Explanations about why working capital management is
significant for a firm generally focus on the relationship between efficiency in working
capital management and firm profitability (Afza and Nazir, 2007; Christopher and
Kamalavalli, 2009; Deloof, 2003). Efficient working capital management includes
planning and controlling of current liabilities and assets in a way that avoids excessive
investments in current assets and prevents from working with few current assets
insufficient to fulfill the responsibilities. It aims at protecting the purchasing power of
assets and maximizing the return on investment.
The success of operations of a firm is determined to a large extent by the method of
administration of its current. It requires continuous management to maintain proper
level in various components of working capital i.e. cash, receivables and inventory etc.
In establishing proper proportions, cash and financial budget may be very useful. Sales
17
expansion, dividend declaration, plant expansion, new product line, increased salaries
and wages, rising price levels etc. put added strain on working capital maintenance.
Due to the poor management and lack of management skills, business fails certainly.
Shortage of working capital, so often advanced as the main cause of failure of industrial
concerns, is nothing but the clearest evidence of mismanagement which is so common.
The prime object of management is to make profit. This accomplishment in most
business depends largely on the manner in which they manage their working capital.
Administration of fixed assets falls within the realm of capital budgeting while the
management of working capital is a continuing function which involves control of every
day and flow of financial resources circulating in the company in one form or the other.
In turn, these decisions are influenced by the trade-off that must be made between
profitability and risk.
Lowering the level of investment in current assets, while still being able to support sales,
would lead the firm to an increase in return on total assets. Smith (1980) first signaled
the importance of the trade offs between the dual goals of working capital management,
i.e., liquidity and profitability. To the extent that the explicit costs of short-term
financing are less then those of intermediate and long-term financing, the greater the
proportion of short-term debt to total debt, the higher is the profitability of the firm.
From another perspective, the current assts of a typical manufacturing firm accounts for
ever half of its total assets. For a distribution company, they account for even more.
Excessive levels of current assets can easily result in a firm is realizing a substandard
return on investment. However firms with too few current assets may incur shortages
and difficulties in maintaining smooth operations (Van-Horne and Wachowicz, 2004).
For small companies current assets and liabilities are the principal source of external
financing. These firms do not have access to the longer term capital markets, other than
to acquire a mortgage on a building. The fast growing but a larger company also makes
use of current liabilities financing. For these reasons the financial manager and staff
18
devotes a considerable portion of their time to working capital matters. The
management of cash, marketable securities, receivable, payables, accruals, and other
means of shot-term financing is the direct responsibility of a financial manager, only the
management of inventories is not. Moreover, these management responsibilities require
continuous day to day supervision. Thus, working capital management is important, for
no other reason than the proportion of the financial managers’ time that must be
devoted to it.
2.7 Effect of Working Capital Policies on Firms’ Profitability: Review of
Previous Studies
Many researchers have studied working capital from different views in different
environments. The following ones are very useful for this research:
In finance literature, there is a long argument on the determinants and the risk/return
tradeoff between the different working capital policies. More aggressive working capital
policies are associated with higher return and higher risk while conservative working
capital policies are concerned with the lower risk and return. In this regard, Belt (1979)
highlighted the determinants of working capital policies and the rewards & risks of an
aggressive working capital policy. The author claimed that there might be two real
determinants of the level of net working capital of a firm. The first determinant is the
operational aspect that describes how much liquidity is needed in the current assets of
the firm whereas the second determinant is the deferability of current liabilities of the
company, which is the ability to postpone or delay the payments to creditors for some
period. The author also asserted that the rewards and risks of an aggressive working
capital policy vary between industries and within industries. Generally, the benefits
might be attained by reducing the holding costs of fast moving inventory, lower
collection costs associated with lower level of receivables and somewhat less costly
short-term debt. However, higher returns of an aggressive working capital policy are
often associated with risk of liquidity as well. The use of large level of current liabilities,
19
i.e. aggressive financing policy of working capital increases the chances of financial
embarrassments that can lead to corporate failure and bankruptcy.
In addition, Carpenter and Johnson (1983) empirically investigated the relationship
between the level of current assets and the operating risk of firms. The sample firms
included were the large firms from various industrial sectors in the United States. The
sample data was collected for a period of four years i.e. 1978-1982. The regression
analysis showed no significant linear relationship between the level of current assets
and revenue systematic risk or operating systematic risk. However, some indications of
a possible non-linear relationship were found which were not highly statistically
significant.
Gentry, et al. (1990) introduced a new concept of weighted cash conversion cycle in
order to examine the working capital management of firms. The weighted cash
conversion cycle measures the weighted number of days the funds are tied up in the
accounts receivables, accounts payables and inventories less number of days payments
are deferred to suppliers of the firms where the weights are calculated by dividing the
amount of cash tied up in each component of working capital by the final value of
product. The proposed weighted cash conversion cycle is an aggregate measure of the
amount and speed that the funds flow through working capital accounts of a firm and
concentrates on the real resources committed to the total working capital process.
Soenen (1993) investigated the relationship between the net trade cycle and return on
investment in United States firms. The study also checked the impact of cash conversion
cycle across industries on the profitability of firms. The annual financial data for 2000
firms and 20 industries had been used for analysis purpose for the period of 1970-1989.
The firms were divided into four quadrants on the basis of the median values of net
trade cycle and return on assets. A chi-square test was applied to measure the
association between the quadrants of firms, which indicated negative relationship
between the length of net trade cycle and return on assets. Furthermore, this inverse
20
relationship between net trade cycle and return on assets was found different across
industries depending on the type of industry. A significance relationship for about half
of industries studied indicated that results might vary from industry to industry.
Lamberson (1995) studied empirically how small firms respond to changes in economic
activities by changing their working capital positions and level of current assets and
liabilities. Small firms were expected to increase the level of current assets and liabilities
as the economy expands. The hypothesis was tested on 50 small firms in United States
and the data about financial statements and economic activities was collected from
Moody’s industrial manual for a period of 1980-1991. Current ratio, current assets to
total assets ratio and inventory to total assets ratio were used as measure of working
capital while index of annual average coincident economic indicator was used as a
measure of economic activity. Correlation analysis was conducted to check the
relationship between the economic expansion/contraction and the level of working
capital while the significance of relationship has been measured by t-test. Contrary to
the expectations, current ratio and quick ratio increased during expansion period while
the other two ratios remained relatively stable during the period of economic expansion.
Overall, the study found that there is very small relationship between changes in
economic conditions and changes in working capital.
Rafuse (1996) analyzed the different aspects of optimal working capital management
and its components. His article argued that attempts to improve working capital
management by delaying the payments to creditors is an inefficient and ultimately
damaging practice, both to its practitioners and to economy as a whole. The study
claimed that altering debtors and creditors levels would rarely produce any net benefit
rather it will harm the sales or the financing options of the firm. The study proposed
that stock reduction strategies based on some “Lean Production” techniques might be
far more effective than any other single working capital management technique.
Reducing stock would produce major financial advantages by improving cash flows,
reducing operational level costs of inventory and reducing capital spending. Moreover,
21
it is further argued that the “Lean” world-class companies are systematically better than
their counterparts in every important aspects and characteristics that makes a company
“Lean” is low stock levels.
As validation of the results found by Soenen (1993) on large sample and with longer
time period, Jose et al. (1996) examined the relationship between aggressive working
capital management and profitability of United States firms. Cash conversion cycle
(CCC) has been taken as a measure of working capital management where a shorter
cash conversion cycle represents the aggressiveness of working capital management
whereas pre-tax return on assets and equity has been used as profitability measures. The
data has been collected for a period of twenty-four years from 1974 through 1993 for
2,718 firms. The relationship between the cash conversion cycle and profitability
measures has been tested through cross-sectional regression analysis. The results
indicated a significant negative relationship between the cash conversion cycle and
profitability indicating that more aggressive working capital management is associated
with higher profitability. The shorter the cash conversion cycle, greater the return on
assets and return on equity.
Bhattacharyya and Raghavacahari (1997) examined the determinants of effective
working capital management in 72 large Indian companies. A questionnaire was mailed
to the mangers to view the perceptions in their working capital management process in
their respective organization. The Discriminate analysis indicated that the prime
determinants of effectiveness of working capital management in order to their relative
importance were: 1) profit after tax as percentage of sales, 2) sales as number of times to
total assets, 3) quick assets as percentage of current liabilities and 4) receivables as
numbers of day’s sales. The authors recommended that the financial managers and
analysts should pay more formal and explicit attention to these four factors while
conducting their financial analysis.
22
Shin and Soenen (1998) empirically examined the relationship between efficiency of
working capital management and the corporate profitability of firms by taking net trade
cycle as a measure of working capital management. The study used 58,985 firm years
record for a period of 20 years from 1975 to 1994. The Pearson linear and Spearman rank
correlation analysis indicated a significant inverse relationship between the net trade
cycle and accounting measure as well as market measure of profitability. The pooled
and cross sectional regression analysis confirmed the results of correlation analysis that
firms with shorter trade cycle earned more profits. However, the negative relationship
between the current ratio and profitability indicate a trade off between liquidity and
profitability of a firm. Therefore, firms can improve corporate profitability by enhancing
efficiency of working capital management by keeping in view the liquidity of firms.
The issue of aggressive and conservative working capital policies on empirical basis has
been discussed by Weinraub and Visscher (1998) who analyzed working capital policies
of 126 industrial firms from 10 diverse industrial groups using quarterly data for a
period of 1984 to 1993. The primary objective was to observe the differences in working
capital policies as well as the long-term stability of working capital policies over time.
Current assets to total assets ratio and current liabilities to total asset ratio were used as
proxies of working capital investment and financing policies respectively. Analysis of
Variance (ANOVA) and Tukey’s HSD (honestly significant difference) tests clearly
indicate significant differences in working capital policies across various industries.
Rank order correlation analysis confirmed the stability of these polices over ten year
period of time. Furthermore, the negative relationship between industry working capital
investment and financing policies indicated that when relatively aggressive working
capital investment policies were followed, they were balanced by relatively conservative
working capital financing policies.
Hall (2002) introduced a “Total” approach to working capital management and argued
that this “Total” approach covered all the company’s activities relating to vendor,
customer and product. Accounts receivables management was termed as Revenue
23
Management, which included searching for customers to collecting cash form them for
credit sales. Inventory management, also named as Supply Chain Management, started
from the forecasting of the customer claimed and ended with the fulfillment of the
forecasted demand. The third working capital component, account payables was
proxied with expenditure management, included the whole process of purchasing from
vendors to pay the cash. The study argued that this integrated or “Total” approach to
working capital management would reduce inefficiencies in the business processes as
well as improve firm performance.
Deloof (2003) investigated the relationship between the working capital management
and corporate profitability for a sample of 1009 large Belgian non-financial firms for the
period of 1992-1996. The cash conversion cycle has been used as a comprehensive
measure of working capital management, whereas gross operating income has been
used as a measure of corporate profitability. In addition, size of the firm, sales growth,
the financial debt and ratio of fixed financial assets to total assets were introduced as
control variables. Using correlation and regression tests he found a significant negative
relationship between gross operating income and cash conversion cycle. On basis of
these results he suggested that managers can create value for shareholders by
maintaining the cash conversion cycle and its components to an optimal level.
Ghosh and Maji (2004) made an attempt to examine the efficiency of working capital
management practices of the Indian cement companies during 1992/93 to 2001/02.
Three measures; performance index of working capital, utilization index of working
capital and efficiency index of working capital were used to measure the overall
efficiency of Indian cement manufacturing firms instead of using some common
working capital management ratios. Setting industry norms as target-efficiency levels of
the individual firms, this paper also tested the speed of achieving that target level of
efficiency by an individual firm during the period of study. Findings of the study
indicated that the Indian Cement Industry as a whole did not perform remarkably well
during this period in terms of working capital management.
24
Eljelly (2004) empirically analyzed 29 Saudi joint stock companies for a period of 19962000 to examine the relationship between liquidity and profitability. The study used net
operating income as dependent profitability measure and cash gap (cash conversion
cycle) and current ratio as independent liquidity measures. The study found that the
cash conversion cycle was of more importance as a measure of liquidity than the current
ratio that affects profitability. A strong negative relationship has been reported between
the liquidity measures and net operating income by Pearson correlation and pooled
regression analysis. Moreover, the size was also affecting the profitability of firms and
these results were stable over the period of study.
Another study by Teruel and Solano (2005) provided empirical evidence of impact of
working capital management on profitability of small and medium sized Spanish firms.
Cash conversion cycle along with its components has been taken as independent
variables whereas return on assets has been used as dependent measure for profitability.
The data set was consisted of 8,872 SMEs covering the period of 1996-2002 was obtained
from ABADEUS database of Spain. A strong negative relationship between return on
assets and cash conversion cycle along with its components i.e. days accounts
receivables, days inventory and days accounts payable was indicated by correlation
analysis. The multivariate regression analysis confirmed this negative relationship that
shortening the cash conversing cycle, firms can generate more profits for shareholders.
The regression results were found significant for negative relation between return on
assets and inventory turnover as well as days accounts receivables. However, impact of
delaying payment to suppliers on return on assets remained inconclusive because it was
not significant at 5 percent level of significance.
Lazaridis and Tryfonidis (2006) investigated the relationship between working capital
management and corporate profitability using quarterly date of 131 firms listed at
Athens Stock Exchange of Greece. Cash conversion cycle has been used as a measure of
working capital management whereas gross profit has been taken as profitability
measure. The size of the firms as measured by natural logarithm of sales, financial debt
25
of firm and fixed financial assets to total assets ratio were used as control variables.
Pearson correlation analysis showed a negative relationship between gross profit and
cash conversion cycle as well as number of days of accounts receivables and inventory
while a positive relationship between gross profit and number of days of accounts
payables. In order to validate the robustness of correlation results, four regressions were
run to examine the individual impact of cash conversion cycle and its components on
gross profit. The regression results provides that cash conversion cycle, number of days
accounts receivables and inventory were negatively while the number of days accounts
payables were positively related to gross profit. All results were statistically significant
at 1 percent level of significance indicating that managers can create profits by keeping
current assets and current liabilities to an optimal level.
Padachi (2006) examined the trends in working capital management and its impact on
firms’ performance for a sample of 58 Mauritian Small Manufacturing Firms operating
in five major industry groups (food and beverages, leather garments, paper products,
prefabricated metal products and wood furniture) which are both registered and
organized as proprietary/private companies. The relationship between working capital
management and corporate profitability was investigated by using panel data analysis
for the period 1998 – 2003. The trend in working capital needs and profitability of firms
are examined to identify the causes for any significant differences between the
industries. The dependent variable, return on total assets defined as profit before
interest and tax divided by total assets, was used as a measure of profitability. The
efficiency ratios, namely accounts receivable period, inventory period and accounts
payable period were used as measures of working capital. The Cash Conversion Cycle
(CCC) was used as a comprehensive measure of working capital. The regressions were
also include the ratio of current liabilities to total assets to measure the degree of
aggressive financing policy, with a high ratio being relatively more aggressive. Sales a
proxy for size (the natural logarithm of sales), the gearing ratio (financial debt/total
assets), the gross working capital turnover ratio (sales/current assets) and the ratio of
26
current assets to total assets were included as control variables in the regressions. The
regression results showed that high investment in inventories and receivables is
associated with lower profitability. An analysis of the liquidity, profitability and
operational efficiency of the five industries showed significant changes and how best
practices in the paper industry have contributed to performance. The findings also
reveal an increasing trend in the short-term component of working capital financing.
Raheman and Nasr (2007) in this research, they have selected a sample of 94 Pakistani
non-financial firms listed on Karachi Stock Exchange for a period of 6 years from 1999 –
2004 to investigate the effect of different variables of working capital management
including the Average collection period, Inventory turnover in days, Average payment
period, Cash conversion cycle and Current ratio on the Net operating profitability of
Pakistani firms. Debt ratio, size of the firm (measured in terms of natural logarithm of
sales) and financial assets to total assets ratio have been used as control variables.
Pearson’s correlation, and regression analysis (Pooled least square and general least
square with cross section weight models) were used for analysis. The results showed
that there was a strong negative relationship between variables of the working capital
management and profitability of the firm. It means that as the cash conversion cycle
increases it will lead to decreasing profitability of the firm, and managers can create a
positive value for the shareholders by reducing the cash conversion cycle to a possible
minimum level. A significant negative relationship between liquidity and profitability
has been founded. They also find that there was a positive relationship between size of
the firm and its profitability. There was also a significant negative relationship between
debt used by the firm and its profitability.
Afza
and
Nazir
(2007)
investigated
the
relationship
between
the
aggressive/conservative working capital policies for seventeen industrial groups and a
large sample of 263 public limited companies listed at Karachi Stock Exchange for a
period of 1998-2003. Using ANOVA and Least Significant Difference (LSD) test, the
study found significant differences among their working capital investment and
27
financing policies across different industries. Moreover, rank order correlation
confirmed that these significant differences were remarkably stable over the period of
study. The aggressive investment working capital policies were accompanied by
aggressive working capital financing policies. Finally, ordinary least square regression
analysis found a negative relationship between the profitability measures of firms and
degree of aggressiveness of working capital investment and financing policies. These
results were further confirmed by Afza and Nazir (2008) on a longer period of time (i.e.
1998-2005) and using market measures of return. Moreover, the later study also took
into consideration the impact of aggressiveness of working capital policies on the risk of
firm. In conformity with Carpenter and Johnson (1983), the study found no significant
relationship between the aggressiveness/conservativeness of working capital policies of
firms and their operating and financial risk.
Ganesan (2007) tried to examine the working capital management efficiency of firms
from telecommunication equipment industry in India. The relationship between
working capital management efficiency and profitability is examined using correlation
and regression analyses. Working capital management efficiency was measured by days
sales outstanding, days inventory outstanding and days payable outstanding. Days of
working capital was also use as a comprehensive measure. The firm’s profitability was
measured using the operating income plus depreciation related to total assets (IA). This
measure is indicator of the raw earning power of the firm’s assets. Another profitability
measure used for this analysis was the operating income plus depreciation related to the
sales (IS).
ANOVA analysis was done to study the impact of working capital
management on profitability. Using a sample of 443 annual financial statements of 349
telecommunication equipment companies covering the period 2001-2007, this study
found evidence that even though “days working capital” is negatively related to the
profitability, it was not significantly impacting the profitability of firms in
telecommunication equipment industry.
28
Samiloglu and Demirgunes (2008) investigated the effect of working capital
management on firms’ profitability for a sample of manufacturing firms listed in
Istanbul Stock Exchange (ISE) for the period 1998-2007. The data was taken from the
quarterly financial statements of the sampled firms from ISE database and 5,843 firmquarter data was used. The dependent variable, firm profitability, was measured by
return on assets. Accounts receivable period, inventory period and cash conversion
cycle were used as proxies for working capital management policies. Like other many
working capital literatures, firm size, firm growth, leverage and fixed financial assets
were used as control variables. The data has been analyzed under a multiple regression
model. The empirical results of the study showed that accounts receivable period,
inventory period and leverage significantly negatively affect profitability of the sample
firms, while firm growth (in sales) significantly and positively. However, it was also
concluded that cash conversion cycle, size and fixed financial assets have no statistically
significant effects on profitability of the sampled firms.
Christopher and Kamalavalli (2009) investigated the relationship between working
capital management and corporate profitability for a sample of 14 corporate hospitals, in
India, listed in the Bombay Stock Exchange (BSE) for the period of 10 years (i.e. 1996/72005/6). The independent variables were Current Ratio, Quick Ratio, Inventory
Turnover Ratio, Debtor’s Turnover Ratio, Working Capital Turnover Ratio, Ratio of
Current Asset to Total Asset, Ratio of Current Assets to Operating Income,
Comprehensive Liquidity Index, and Net Liquid Balance. The dependent variable
‘profitability’ was measured in terms of Return on Investment (ROI) ratio. Size,
Leverage and Growth were also used as control variables. Working capital management
variables associated with ROI was examined through Correlation analysis. Impact of
working capital management variables on ROI was assessed through multiple
regression analysis. The most prominent variables that influence ROI were studied by
employing Step-wise regression analysis. Direct and indirect effect of selected variables
on ROI was analyzed through Path analysis. Correlation analysis reveals that eight
29
variables (inventory turnover ratio, debtors turnover ratio, working capital turnover
ratio, current assets to total assets ratio, comprehensive liquidity index, net liquid
balance, growth rate and size) were significantly positively associated with ROI. From
regression analysis it is evident that an increase of one unit in current ratio, cash
turnover ratio, current assets to operating income and leverage decreases profitability.
Current ratio, quick ratio, cash turnover ratio, current assets to operating income and
leverage were showed negative association with return on investment. Step wise
regression analysis has identified seven prominent variables (cash turnover ratio,
leverage, debtors turnover ratio, size, current ratio, growth rate and quick ratio) that
were significantly influence profitability. Path analysis showed ‘quick ratio’ has the
highest direct effect on profitability while ‘current ratio’ has the least direct effect.
Nobanee (2009) examined the relationship between working capital management and
firm’s profitability for a sample of 5802 non-financial firms listed in the New York Stock
Exchange, American Stock Exchange, NASDAQ Stock Market and the Over the Counter
Market for the period of 1990-2004 (87030 firm-year observations). To measure working
capital management efficiency, optimal cash conversion cycle which is an additive
function of optimal inventory conversion period, optimal receivable collection period
and optimal payable deferral period was used. Profitability was measured by operating
income to sales ratio. To investigate the relationships between chosen variables a
Generalized Method of Moment System Estimation (GMM) applied to dynamic panel
data. In contrast with other findings, the estimated coefficients showed that the length of
the cash conversion cycle, the length of the receivable collection period and the length of
the inventory conversion period had positive impact rather than negative impact on the
company’s profitability. The results also showed that the payable deferral period had
significant negative impact on profitability instead of having a positive impact as
reported on other existing literatures. In addition, the results showed that an increase in
the quick ratio was negatively associated with firm’s profitability, this result certify the
traditional trade off between profitability and liquidity. Finally, this study was
30
suggested an optimal cash conversion cycle as more accurate and comprehensive
measure of working capital management that maximizes sales, profitability and market
value of firms.
Sen and Oruc (2009) in their study aimed to determine the relationship between
efficiency levels of working capital management and return on total assets of 49
production firms being traded in ISE (Istanbul Stock Exchange) by using 3 month-table
data of 15 years (i.e. 1993-2007) for the total of 60 periods. They tried to explain the
relationship between different indicators relating to efficiency in working capital
management (cash conversion cycle, net working capital level, current ratio, accounts
receivable period, inventory period) and return on total assets through two models.
According to the results, in terms of both models, in all the firms involved in the study
and sectors there is significant negative relationship between cash conversion cycle, net
working capital level, current ratio, accounts receivable period, inventory period and
return on total assets. In this study it was concluded that finance directors positively
affect firm profitability through efficiency increase in management of this assets group.
Zariyawati, et al. (2009) examined the relationship between working capital
management and firm profitability for a sample of 148 firms listed in Bursa Malaysia.
This study was used panel data of 1628 firm-year for the period of 1996-2006 that consist
of six different economic sectors. Cash conversion cycle was used as measure of working
capital management. The coefficient results of Pooled OLS regression analysis was
provide a strong negative significant relationship between cash conversion cycle and
firm profitability. This reveals that reducing cash conversion period results to
profitability increase. Like most of other working capital literatures, this study was also
suggested that, in purpose to create shareholder value, firm manager should concern on
shorten of cash conversion cycle till optimal level is achieved.
31
In Africa, a little work has been found in finance literature, specifically with reference to
short-term financial management and working capital. In this regard, Smith and
Begemann (1997) examined the trade off between the liquidity and profitability of firm
by investigating the association between return on investment and alternative measures
of working capital. The study evaluated the association between traditional and
alternative working capital measures and return on investment (ROI), specifically in
industrial firms listed on the Johannesburg Stock Exchange (JSE) for a period of 1984 to
1993. The problem under investigation was to establish whether the more recently
developed alternative working capital concepts showed improved association with
return on investment to that of traditional working capital ratios or not. Results
indicated that there were no significant differences amongst the years with respect to the
independent variables. The results of their step-wise regression corroborated that total
current liabilities divided by funds flow accounted for most of the variability in Return
on Investment (ROI). The statistical test results showed that a traditional working
capital leverage ratio, current liabilities divided by funds flow, displayed the greatest
associations with return on investment. Well known liquidity concepts such as the
current and quick ratios registered insignificant associations whilst only one of the
newer working capital concepts, the comprehensive liquidity index, exhibited strong
negative correlation with return on investment as 5 percent level of significance.
A study by Enyi (2005) examined the relationship between the operational size of the
firm and the adequacy of the working capital requirements in Nigeria. Relative solvency
ratio has been used to measure the level of working capital that can be considered
adequate for the firm size and operational level. A relative solvency ratio greater than
one was considered to be adequate for working capital level requirements relative to the
operational size of the firms. The data has been collected from the annual published
repots of 25 companies listed in Nigeria Stock Exchange together with the interviews of
selected officials of the firms. T-test has been applied to compare the relative solvency
ratio and return on capital employed as the performance measure of firms having
32
relative solvency ratio greater than one with those that were less than one. The results
indicated that firms having relative solvency ratio greater than 1 i.e. adequate working
capital relative to its operational size perform better than firms who have inadequate
working capital.
Falope and Ajilore (2009) provided empirical evidence about the effects of working
capital management on firms’ profitability by using secondary data sources from annual
reports and financial statements of a sample of 50 non-financial firms listed in Nigerian
Stock Exchange for the time period 1996-2005. The dependent variable, firms’
profitability, was measured by return on assets, defined as net income divided by
average book value of assets. With regards to the independent variables, number of
days of accounts receivable, number of days of inventory, number of days of accounts
payable and cash conversion cycle were used to measure working capital management.
Size (defined as logarithm of assets), sales growth, debt and economic cycle (annual
GDP growth rate) were also used as control variables. The study utilized panel data
econometrics in a pooled regression with fixed effect models, where time-series and
cross-sectional observations were combined and estimated. Significant negative
relationship was found between profitability and average collection period, inventory
turnover in days, average payment period and cash conversion cycle. According to the
researchers, a negative relationship between number of days of accounts payable and
profitability was consistent with the view that less profitable firms wait longer to pay
their bills. In this case, profitability affects the account payables and vice versa.
Furthermore, the study found no significant variations in the effects of working capital
management between large and small firms. Finally, the researchers were suggested
that managers can create value for their shareholders if they manage their working
capital in more efficient ways by reducing the number of days of accounts receivable
and inventories to a reasonable minimum.
Another study by Mathuva (2009) investigated the impact of working capital
management components (average collection period, inventory conversion period, and
33
average payment period) on corporate profitability measured by the net operating profit
for a sample of 30 firms listed on Nairobi Stock Exchange (NSE) for the periods 1993 to
2008. Both the pooled OLS and the fixed effects regression models were used. The key
findings from the study were: (1) there exists a highly significant negative relationship
between the time it takes for firms to collect cash from their customers (accounts
collection period) and profitability. This means that more profitable firms take the
shortest time to collect cash from their customers; (2) there exists a highly significant
positive relationship between the period taken to convert inventories into sales (the
inventory conversion period) and profitability. This means that firms which maintain
sufficiently high inventory levels reduce costs of possible interruptions in the
production process and loss of business due to scarcity of products. This reduces the
firm supply costs and protects them against price fluctuations: (3) there exists a highly
significant positive relationship between the time it takes the firm to pay its creditors
(average payment period) and profitability. This means that the longer a firm takes to
pay its creditors, the more profitable it is. Based on the findings, the management of a
firm can create value for their shareholders by increasing inventories to a reasonable
level, taking long to pay creditors to the optimum level and reducing the cash
conversion cycle to its minimum.
Finally, no research has been done in spite of the learned impact in the area of the
provision of empirical evidence in support of the effect of management of working
capital policies on profitability of firms in Ethiopia in general and in Tigray region in
particular. Given this lack of empirical studies, it is hoped that this study fill a gap and
provide useful support for better understanding of the effect of management of working
capital policies on profitability of Manufacturing Private limited companies in Tigray
regional state, Ethiopia.
34
2.8 Conceptual Framework for Analysis
From the literature review mentioned above, the researcher has developed the following
schematic representation of the conceptual framework/ model for this study:
Figure1: Conceptual framework for analysis
Working Capital Investment Policy
Working Capital Financing Policy
Current Liability to Total Assets Ratio
Accounts Receivable Period
Inventory Holding Period
Accounts Payable Period
Cash Conversion Cycle
Current Assets to Total Assets Ratio
FIRMS’
PROFITABILITY:
Return on Assets
Return on Equity
Operating Profit Margin
Liquidity
Control Variables
Current Ratio
Firm Size
Quick Ratio
Firm Growth Rate
Financial Leverage
GDP
Source: Researcher’s own design
35
CHAPTER III
METHODOLOGY
3.1 Research Design
The explanatory type of study with a quantitative approach was employed to analyse
the data collected. The research design used in this study is a pooled panel data analysis
of cross-sectional and time series data. Pooled panel data analysis, also called the
constant coefficients model is one where both intercepts and slopes are constant, where
the cross section firm data and time series data are pooled together in a single column
assuming that there is no significant cross section or temporal effects (Gujarati, 2003).
This study is conducted on selected sample of firms in Tigray with the intention to
provide evidence for the effects of the management of working capital policies on the
profitability of private limited companies in Tigray.
3.2 Data Source and Collection Methods
The data required for the purpose of analysis was obtained from secondary sources;
audited financial statements including balance Sheet and Income Statement of sample
companies for a period of five years (2005-2009). The researcher considers five years
because of limited number of firms having an operating life of more than five years.
Most of the required data was obtained from the financial statements submitted to the
Ethiopian Revenues and Customs Authority (ERCA) Mekelle regional branch, for
income tax purpose. However, due to incompleteness of data obtained from ERCA
some of the data used was obtained directly from the respective companies.
3.3 Sampling Design
The total population of the study is all manufacturing private limited companies located
and operating with in the boundary of Tigray Regional State. In selecting firms included
in this study, convenience and purposive sampling designs have been used. Tigray
36
region is found to be convenient to obtain the required data with the limited time and
fund available for the study. The sampling method used is also designed to be
purposive due to the following requirements in order to be included in the sample.
The first criterion used in selecting sample units to be included in the study is holding a
complete 6 years financial statement data. The data pertaining to year 2004 is only used
to compute the variable growth whose indicator is change in total sales and it is used to
compute the sales growth only for the year 2005 of all observations.
The researcher further conducted two stage restriction criterions to arrive at defining the
study population. The study first selected the manufacturing industry sector from the
business classification, i.e. agriculture, industry and service, according to data from
Mekelle branch Ministry of Trade Industry and Transport. In so doing, the sample
considers companies that are engaged in the manufacturing sector of the economy only.
The data from the bureau also shows that there have been 210 manufacturing industry
sector firms of various sizes that took business license in the year (2005) 1997 E.C and
before. (See appendix A).
The researcher then made the second level sample restriction that the manufacturing
companies need to hold the legal status of ‘Private Limited Company’. In this case,
based on 2009 (2001E.C.) data from Ethiopian Revenues and Customs Authority (ERCA)
regional Mekelle branch, 80 private limited companies were running businesses in
Tigray Regional State.
The above restrictions are made in an attempt to avoid bias that may result from, first,
industrial classification i.e. since firms operating in different class of economy have
different decision criteria in selecting sources of funds needed for executing investment
opportunities and different working capital requirements. In order to mitigate this
problem the researcher limited the study population only to those companies engaged
in manufacturing industry.
37
Secondly, the approach followed by tax authority in collecting tax from business
organizations in Ethiopia is progressive in nature. Therefore; it basically uses size of
sales turnover as its criteria for categorizing business firms. Since different tax category
firms have different capacity in appropriating tax shield advantage from their capital
structure choice (Equity versus debt financing), in an effort to minimize this size bias,
researcher includes those firms having a legal status of private limited company only in
constructing sample elements.
According to the data from Ethiopian Revenues and Customs Authority (ERCA) and
interview with regional officials, all firms operating in the boundary of Federal
Democratic Republic of Ethiopia with a legal status of ‘Private Limited Company’ are
automatically eligible for paying Value Added Tax (VAT). The Ethiopian taxation law,
Proclamation 246/2000, for Value Added Tax (VAT) clearly specifies VAT payers as
firms having an annual sales turnover of more than Birr 500,000.
The researcher tried to make the sample representative of the population-manufacturing
private limited companies operating in the boundary of Tigray Regional State. The
researcher, therefore, selected and collected 16 companies’ financial statements of which
only 11 (13.75% of the target population) are found workable. Since most of the eighty
companies have started their operation on and after the year 1998 E.C. further increase
of sample size becomes impossible.
The researcher also used a stratified sampling technique where each sample element
will be selected purposively in objective to make the sample representative of available
strata-sub classifications in the manufacturing industry as well as the area distribution.
3.4 Data Analysis
Descriptive statistics were used as the first step in the analysis and it was use to describe
relevant aspects of observable facts about the variables and provide detailed
information about each relevant variable. At this stage, mean, standard deviation,
38
maximum and minimum values of the required variables have been computed. The data
obtained were also analyzed by using two quantitative analysis methods. First, Pair
wise Correlation analysis was used to measure the degree of association between the
dependent variables and explanatory variables. Second, linear panel data regression
modes were used to analyze the causal relationships of profitability variables with
working capital investment and financing policies, liquidity and control variables. “By
combining time series of cross-section observations, panel data gives more informative
data, more variability, less co-linearity among variables, more degrees of freedom and
more efficiency” ( Baltagi cited by Gujarati 2003:637). STATA SE 9 software was used for
the purpose of analysis and tables are used to present the results from the analysis.
3.5 Description of Variables and Research Hypotheses
In order to analyze the effects of management of working capital policies on firms’
profitability the researcher identifies key variables that indicate profitability, working
capital investment and financing policies, liquidity and other factors that influence
profitability. The chosen variables include dependent, independent and some control
variables.
3.5.1 Dependent Variables
Dependent Variables are variables that are used to measure the profitability of firms.
Due to the absence of secondary market in Ethiopia it is impossible to use market
indicators such as share price, only accounting measures of profitability were used to
analyze the effect of working capital policies on the profitability of firms. In the
accounting measures, Return on Assets (ROA), Return on Equity (ROE) and Operating
Profit Margin (OPM) are best known and most frequently used profitability measures
(Ross et al, 2000). To establish a true relationship between the operating “success” or
“failure” of firms and working capital policies and to avoid the effect of tax incentives
(if available), Earning Before Interest and Tax (EBIT) was used as a base to calculate
return on assets and operating profit margin as follows:
39
Return on Assets (ROA) = Earning Before Interest and Tax (EBIT)
Total Assets (TA)
Operating Profit Margin (OPM) = Earning Before Interest and Tax (EBIT)
Net Sales (NS)
To measure the return to the equity owners, earning before tax was used. The formula
is:
Return on Equity (ROE) = Earning Before Tax (EBT)
Total Equity (TE)
3.5.2 Independent Variables and Respective Research Hypotheses
With regard to the independent variables, Accounts Receivable Period (ARP), Inventory
Holding Period (IHP) and Accounts Payable Period (APP) were used to measure
specific working capital investment policy. Moreover, Cash Conversion Cycle (CCC)
and Current Assets to Total Assets Ratio (CATAR) were used as compressive measures
of working capital investment policy. Current Liabilities to Total Assets Ratio (CLTAR)
was used as a measure of working capital financing policy whilst the two conventional
measures, Current Ratio (CR) and Quick Ratio (QR), were used as indicators of liquidity
(Eljelly, 2004; Lazaridis and Tryfonidis, 2006; Padachi, 2006; Raheman and Nasr, 2007).
Accounts Receivable Period (ARP), was used as proxy for Collection Policy, and
represents the average time it takes to collect payments from customers from sales of
goods and services. The longer the accounts receivable period, the higher will be the
investment in accounts receivable. Theoretically, the higher the investment in account
receivable, the lower will be the profitability. Thus, the researcher has formulated the
following testable hypothesis:
40
H01: There is significant inverse relationship between accounts receivable period and profitability
of firms.
The formula used to calculate the account receivable period is:
Accounts Receivable Period (ARP) = [Ending Accounts Receivable /Net Sales] X 365 days
Inventory Holding Period (IHP), was used as proxy for the Inventory Policy, and stands
for the average time it takes to acquire and sell inventory. The longer the inventory
storage period, the higher will be the investment in inventory. In the same manner, the
higher the amount invested in inventory, the lower will be the profitability of firms. The
hypothesis of the researcher in this regard was:
H02: There is significant negative relationship between inventory holding period and profitability.
Inventory Holding Period was calculated by the following formula:
Inventor Period (IP) = [Ending Inventories /Costs of Good Sold] X 365 days
Accounts Payable Period (APP), was used as proxy for the Payment Policy, and
represents the average time between purchases of inventory and payment for it. The
higher the value, the longer it takes to settle payment commitments to suppliers and
hence, the lower will be the investment in working capital.
Therefore, other hypothesis was:
H03: There is a significant positive relationship between accounts payable period and profitability.
The following formula was used to calculate Accounts Payable Period:
Account Payable Period (APP) = [Ending Accounts Payable/ Net Purchases] X 365 days
In addition, the Cash Conversion Cycle (CCC) and Current Assets to Total Assets Ratio
(CATAR) were used as comprehensive measures of working capital investment policy.
The Cash Conversion Cycle (CCC) represents the average time between cash
41
disbursement for inventory and cash collection from receivables. The shorter the Cash
Conversion Cycle (CCC), the lower will be the investment in inventories and
receivables. The longer the Cash Conversion Cycle the greater the investment in current
assets hence the greater the need for financing of current assets. The hypothesis was,
thus:
H04: There is strong negative relationship between cash conversion cycle and profitability of
firms.
The formula to calculate the Cash Conversion Cycle (CCC) is:
Cash Conversion Cycle (CCC) = Accounts Receivable Period (ARP) + Inventory
Period (IP) – Account Payable Period (APP)
Current Assets to Total Assets Ratio (CATAR) represent the proportion of current assets
in the total assets of the firm. The higher the value, the higher will be the investment in
current assets. Hypothesis in this regard was:
H05: There is strong inverse relationship between current assets to total assets ratio and
profitability of firms.
Current Assets to Total Assets Ratio is calculated by the following formula:
Current Assets to Total Assets Ratio (TCATAR) =Total Current Assets (TCA)
Total Assets (TA)
To measure working capital financing policy efficiency Current Liabilities to Total
Assets Ratio, which measures the Degree of Aggressiveness in Working Capital
Financing, was used (Weinraub and Visscher, 1998; Afza and Nazir, 2007). Degree of
Aggressiveness in working capital financing (DOAWCF) represents the extent to which
the firm uses current liabilities to finance its working capital. The higher the value, the
more the firm is aggressive in using current liabilities. Theoretically, aggressive working
42
capital financing police relate with higher profitability. Thus, other research hypothesis
was:
H06: There is significant positive relationship between current liabilities to total assets ratio and
profitability of firms.
The following formula was used to calculate current liabilities to total assets ratio
Current Liabilities to Total Assets Ratio (CLTAR) = Total Current Liabilities (TCL)
Total Assets
Liquidity, one of the two objectives of working capital management is liquidity. In this
study, the researcher has tried to examine the relationship between the two objectives of
working capital management policies: liquidity and profitability. Liquidity refers to the
ability to meet current liabilities from available current assets. In this study the
traditional measures of liquidity: Current Ratio (CR) and Quick Ratio (QR) were used.
The hypotheses here were that:
H07: There is significant negative relationship between current ratio and profitability of firms.
H08: There is significant negative relationship between quick ratio and profitability of firms.
The formulas are:
Current Ratio (CR) =
Current Assets
Current Liabilities
Quick Ratio (QR) = Current Assets- Ending Inventory
Current Liabilities
43
3.5.3 Control Variables
In order to have a reliable analysis of the effect of working capital management policies
on profitability, it is common in working capital literature to use some control variables
to account for various factors that may influence profitability of firms (Deelof, 2003;
Eljelly, 2004; Lazaridis and Tryfonidis, 2006; Padachi, 2006; Afza and Nazir, 2007).
Accordingly, together with the above working capital variables, some control variables
that are specific to firms and general to the economy as a whole were taken into account
in this study. Firm Size (FS), Firm Growth Rate (FGR) and Financial Leverage (FL) are
control variables that are specific to the firm. In order to account for Firm Size (FS), as
used by different prior researchers, the natural logarithm of sales was used (Deloof,
2003; Eljelly, 2004; Padachi, 2006; Raheman and Nasr, 2007). As a proxy for Firm Growth
Rate (FGR) change in annual sales [(Salest−Salest-1)/Salest-1] was used. Total debt to total
assets ratio was used as a proxy for Financial Leverage (FL). Finally, since change in
economic conditions affect operating efficiency of firms and tend to be reflected in firms’
profitability (Lamberson 1995), GDP Growth Rate (GDP) of the country was also used
as a control variable.
3.6 Model Specifications
As mentioned above, the effect of working capital management policies on firms’
profitability has been estimated by using quantitative models. The general model
formulated was as follows:
Yi = β0 +Σ βiXi + εi
Where
Yi are the ith
observation of dependent variables (ROA, ROE and OPM)
β0 is the intercept of the equation
44
βi are coefficients of Xi variables
Xi are the different independent variables
εi is the error term
Specifically, when the above general model is converted into the specified Variables of
this study the following regression equations were run to estimate the impact of
working capital policies on the profitability of selected companies:
Accounts Receivable Period and Profitability Measures:
ROA i = β0 + β1(ARPi) + β2(FSi) + β3(FGRi) + β4(FLi) + β5(GDPt) + ε………….(1)
ROE i = β0 + β1(ARPi) + β2(FSi) + β3(FGRi) + β4(FLi) + β5(GDPt) + ε…………..(2)
OPM i = β0 + β1(ARPi) + β2(FSi) + β3(FGRi) +β4(FLi) + β5(GDPt) + ε…………..(3)
Inventory holding period and profitability measures:
ROA i = β0 + β1(IHPi) + β2(FSi) + β3(FGRi) + β4(FLi) + β5(GDPt) + ε……………(4)
ROE i = β0 + β1(IHPi) + β2(FSi) + β3(FGRi) + β4(FLi) + β5(GDPt) + ε…………….(5)
OPM i = β0 + β1(IHPi) + β2(FSi) + β3(FGRi) + β4(FLi) + β5(GDPt) + ε……………(6)
Accounts payable period and profitability measures:
ROA i = β0 + β1(APPi) + β2(FSi) + β3(FGRi) + β4(FLi) + β5(GDPt) + ε…………..(7)
ROE i = β0 + β1(APPi) + β2(FSi) + β 3(FGRi) + β4(FLi) + β5(GDPt) + ε…………..(8)
OPM i = β0 + β1(APPi) + β2(FSi) + β3(FGRi) + β4(FLi) + β5(GDPt) + ε…………..(9)
Cash Conversion Cycle and Profitability Measures:
ROA i = β0 + β1(CCCi) + β2(FSi) + β3(FGRi) + β4(FLi) + β5(GDPt) + ε…………(10)
ROE i = β0 + β1(CCCi) + β2(FSi) + β3(FGRi) + β4(FLi) + β5(GDPt) + ε………….(11)
45
OPM i = β0 + β1(CCCi) + β2(FSi) + β3(FGRi)+ β4(FLi) + β5(GDPt) + ε………….(12)
Current Assets to Total Assets Ratio and Profitability Measures:
ROA i = β0 + β1(CATARi) + β2(FSi) + β3(FGRi) + β4(FLi) + β5(GDPt) + ε……..(13)
ROE i = β0 + β1(CATARi) + β2(FSi) + β3(FGRi) + β 4 (FLi) + β5(GDPt) + ε……..(14)
OPM i = β0 + β1(CATARi) + β2(FSi) + β3(FGRi)+ β4(FLi) + β5(GDPt) + ε………(15)
Current Liabilities to Total Assets Ratio and Profitability Measures:
ROA i = β0 + β1(CLTARi) + β2(FSi) + β3(FGRi)+ β 4 (FLi) + β5(GDPt) + ε……...(16)
ROE i = β0 + β1(CLTARi) + β2(FSi) + β3(FGRi) + β4(FLi) + β5(GDPt) + ε…….....(17)
OPM i = β0 + β1(CLTARi) + β2(FSi) + β3(FGRi) + β 4 (FLi) + β5(GDPt) + ε……..(18)
Current Ratio and Profitability Measures:
ROA i = β0 + β1(CRi) + β2(FSi) + β3(FGRi) + β 4 (FLi) + β5(GDPt) + ε……...........(19)
ROE i = β0 + β1(CRi) + β2(FSi) + β3(FGRi) + β4(FLi) + β5(GDPt) + ε……..............(20)
OPM t = β0 + β1(CRi) + β2(FSi) + β3(FGRi) + β4(FLi) + β5(GDPt) + ε…….............(21)
Quick Ratio and Profitability Measures:
ROA i = β0 + β1(QRi) + β2(FSi) + β3(FGRi) + β4(FLi) + β5(GDPt) + ε…….............(22)
ROE i = β0 + β1(QRi) + β2(FSi) + β3(FGRi) + β4(FLi) + β5(GDPt) + ε……..............(23)
OPM i = β0 + β1(QRi) + β2(FSi) + β3(FGRi)+ β4(FLi) + β5(GDPt) + ε……..............(24)
Where:
ROA i = Return on Assets of observation i
ROE i = Return on Equity of observation i
OPM i = Operating Profit Margin of observation i
46
ARPi = Accounts Receivable Period of observation i
IHP i = Inventory Holding Period of observation i
APPi= Accounts Payable Period of observation i
CCCi= Cash Conversion Cycle of observation i
CATARi = Current Assets to Total Assets Ratio of observation i
CLTARi = Current Liabilities to Total Assets Ratio of observation i
CRi = Current Ratio of observation i
QRi= Quick Ratio of observation i
FSi = Firm Size of observation i
FGRi = Firm Growth Rate of observation i
Fli = Financial Leverage of observation i
GDPt = Gross Domestic Product Growth Rate of Ethiopia for time period t
ε =error term of the model
β0 = intercept
47
CHAPTER IV
RESULTS AND DISCUSSION
4.1. Demographic Distribution of Sample Firms
The geographical area of the sampled firms includes the following towns; Mekelle,
Adwa, Adigrat, Quiha and Wukro and they are from cement and construction materials,
Industrial Engineering, Leather, Alcohol, Flour, plastic, Stone Crasher, Textile and
pharmaceutical industries( See appendix A).
4.2 Descriptive Statistics for the Study Variables
In this section the results from descriptive statistics are discussed. The descriptive
statistics was used in order to get insight into the trend of working capital management,
profitability, liquidity and other chosen variables among the sample firms and it is used
as base to forward recommendations after determining the relationship between the
variables from correlation and regression analyses.
Table 4.1 presents the descriptive statistics of the sample firms including the mean
distribution, standard deviations, minimum and maximum values of study variables for
the study period i.e. 2005 to 2009. The study has used fifteen variables for the analysis
purpose including twelve independent variables and three dependent profitability
measures. Six independent variables are proxies for working capital investment and
financing policies of the sample firms. Two independent variables were used to measure
liquidity. Other four independent control variables used are firm size as measured by
the natural logarithm of sales, firm growth rate measured by the relative change in sales
as compared to previous year, leverage of the firms and the GDP growth rate of
Ethiopia.
48
From table 4.1, the mean value of return on asset is 5.22 percent and the standard
deviation is 16.52 percent. The minimum value of return on asset is -22.03 percent while
the maximum is 49.01 percent. The profitability of the sample firms, on average, is 1.29
percent as measured by return on equity. It deviates from the mean value to both sides
by 37.41 percent. The minimum and maximum values are -125.18 percent and 88.59
percent respectively. Operating profit margin, on the other hand, is -5.73 percent on
average with standard deviation of 40.35 percent. It means that, on average, out of one
birr of sales 5.73 cents are losses and these results may be deviated to both sides by 40.35
percent. The minimum operating profit margin among the sample firms is -171.82
percent and the maximum is 56.42 percent.
Table 4.1: Descriptive Statistics for the Study Variables
Variable
Obs
ROA
55
ROE
55
OPM
55
CR
55
QR
55
ARP
55
IHP
55
APP
55
CCC
55
CATAR
55
CLTAR
55
FS
55
FG
55
FL
55
GDP
55
Source: STATA data summary
Mean
Std.Dev.
.0522218
.1651699
.0128945
.3740873
-.0573164
.4034827
5.338545
12.44557
2.966982
5.731446
120.4364
166.7682
314.2238
398.6511
120.2178
156.5305
313.5207
558.2731
.4810218
.2060634
.2441176
.1845109
16.82964
2.007783
1.153084
4.438855
.7177382
.6434607
10.76
1.010427
statistics result based on
Min
Max
-.2203
.4901
-1.2518
.8859
-1.7182
.5642
.31
89.94
.011
39.72
0
810.98
0
1598.52
0
586.1
-315.64
2264.77
.0425
.7935
.0013
.7252
11.8
20.87
-.3577
31.8182
.0068
3.5163
8.9
11.6
annual reports of sample
firms for the study period- Appendix B Attach the Financial Statements
To study the relationship between profitability and liquidity, the researcher has used the
traditional liquidity measures, current and quick ratios. The average current ratio for the
sampled Tigray Manufacturing Private Limited Companies is 5.34, which is by far
49
greater than the preferred current ratio, as a rule of thumb, 2. The standard deviation
12.45 indicates a wide variation in current ratio among the sampled companies. The
minimum and the maximum values of current ratio are 0.31 and 89.94 respectively.
Regarding quick ratio, the mean value is 2.97, which is also highly greater than the
standard quick ratio 1 (in finance literature, as a rule of thumb the preferred/standard
quick ratio is 1). The standard deviation is 5.73. The minimum value of quick ratio is
0.011 while the maximum is 39.72.
In the same way, the descriptive statistics for working capital investment and financing
policies are also presented in the same table. There are three specific variables as
measures of efficiency of working capital investment policy, namely, accounts
receivable period, inventory holding period and accounts payable period. Accounts
receivable period, a proxy for collection policy, is 120 days on average. It means that
firms in the sample wait for 120 days on average to collect cash from credit sales. The
standard deviation 167 days, however, indicates the existence of large difference in
accounts receivable period among the sampled firms. Account receivable period ranged
from zero to 811 days among the sampled firms.
Inventory holding period, a proxy for inventory policy, is 314 days on average. That is,
firms in the sample take on average 314 days to sell inventory. The standard deviation
of inventory holding period is 399 days with zero and 1599 days as minimum and
maximum values respectively. Here, the maximum time, 1599 days, to convert
inventory into sales is a very long period. Accounts payable period, a proxy for payment
policy, is 120 days on average with standard deviation of 157 days. The minimum value,
zero days, indicates that the firm makes no credit purchases. The maximum time taken
by a firm for the purpose of payment of accounts payables is 586 days.
In addition to the above three specific variables, other two variables are used as
comprehensive
measures
of
the
efficiency
of
working
capital
asset
management/investment policy. Cash conversion cycle, one of the two comprehensive
50
measures, is 314 days on average and the standard deviation is 558 days. The minimum
value of -316 days shows that a firm records a large inventory turn-over and/or cash
collections from credit sales before making a single payment for credit purchases. It
means that the accounts receivable period and/or the inventory holding period are very
short and/or the accounts payable period of the firm is very long. On the other hand,
the maximum time for cash conversion period is 2265 days which is a very long period.
The other compressive measure of working capital investment policy used is the
proportion of current assets in the total assets of firms. It measures the firms’ degree of
aggressiveness/conservativeness in working capital investment. The lower the amount
of the investment in current assets, the more aggressive is the firm in working capital
investment. Here, the current assts to total assets ratio is 48.10 percent on average. It
means that in the sampled firms, the amount of current assets represent, on average,
48.10 percent of the total assets invested. This amount can deviate by 20.61 percent to
both sides. The minimum value is 4.25 percent and this value related with highly
aggressive condition while the maximum value of current assets to total assets ratio is
79.35 percent which represent the higher conservative condition in the sampled firms
during the study period. The average value of 48.10 percent is in middle of the two
extreme observations and shows that on average manufacturing private limited
companies in Tigray are neither too mach conservative nor aggressive while managing
their current assets.
In measuring working capital financing policy, current liabilities to total assets ratio is
used. It measures the firm’s degree of aggressiveness/conservativeness in financing its
working capital requirements. The higher the value of current liabilities to total assets
ratio, the more aggressive is the firm in financing its working capital requirements. The
average current liabilities proportion in financing the total assets of the sampled
companies is 24.41 percent and the standard deviation is 18.45 percent. The minimum
value is 0.13 percent which represents the more conservative condition in working
capital financing while the maximum is 72.52 percent which indicates highly aggressive
51
approach in working capital financing. When we look at the average current assets
proportion in total assets of sampled firms (48.10 percent) and the average proportion of
current liabilities used in financing total assets (24.41 percent) together, the sampled
firms are relatively conservative in financing their working capital requirements than in
their investment policy.
Table 4.1 also includes the descriptive statistics of control variables used in the study.
The first control variable, firm size, as measured by the natural logarithm of annual
sales, is 16.83 on average (Br. 20,378,683.78 in terms of annual sales) and the standard
deviation is 2.01. The minimum and maximum values of firm size, as measured by the
natural logarithm of sales, are 11.8 and 20.87 respectively. The second control variable,
firm growth rate is 115.31 percent on average, as measured by changes in annual sales.
This indicates that there is a higher sales growth rate among the sampled firms.
However, there is also higher deviation, 443.98 percent, from mean value of sales
growth to both directions. The sales growth among the sampled firms is ranged from 37.77 percent to 3181.82 percent. The third control variable, financial leverage is 71.77
percent on average and the standard deviation is 64.35 percent. Finally, the annual
average GDP growth rate of Ethiopia is 10.76 percent for the study period. The lower
and higher annual GDP growth rates during the study period are 8.9 percent and 11.6
percent.
4.3 Correlation Analysis: Relationship between Working Capital Policies
and Firms’ Profitability
The descriptive statistics showed the average values, with their respective variations,
and the minimum and maximum values of profitability measures, proxy variables for
working capital investment and financing policies and other chosen variables of the
firms in the sample. The correlation analysis was done to analyze the relationship
between the working capital assets management/investment and financing policies and
profitability. Moreover, correlation analysis was also done to examine the relationship of
52
profitability with liquidity and the control variables. To examine the relationship among
these variables, Pearson correlation coefficients were calculated. In this section of the
study the results and discussions of the correlation analysis are presented.
Table 4.2: Correlation Analysis of Profitability with Accounts Receivable Period
and Control Variables
ROA
ROE
OPM
ARP
FS
FGR
FL
Source:
ROA
ROE
OPM
1.0000
0.8207
1.0000
(0.0000)
0.7875
0.8813
1.0000
(0.0000)
(0.0000)
-0.3808
-0.6728
-0.6185
(0.0041)
(0.0000)
(0.0000)
0.3996
0.3278
0.2284
(0.0025)
(0.0146)
(0.0935)
-0.0470
-0.0032
-0.0036
(0.7333)
(0.9814)
(0.9790)
-0.3199
-0.2030
-0.4491
(0.0173)
(0.1372)
(0.0006)
STATA correlation results based on
ARP
FS
FGR
FL
1.0000
-0.0027
1.0000
(0.9844)
1.0000
0.0943
-0.0213
(0.4935) (0.8772)
0.1570
0.2291
-0.0309 1.0000
(0.2523) (0.0924) (0.8231)
annual reports of sample firms for the
study period
Above, Table 4.2 shows the correlation matrix that predicts the likely relationship of the
three profitability measures with accounts receivable period and the control variables of
the study. The P-values are listed in parenthesis. In view of the fact that efficient
working capital management is expected to improve companies’ profitability, one
should expect negative correlation between accounts receivable period and the
profitability measures i.e. return on assets, return on equity and operating profit margin.
Initially, the research hypothesis was that there will be a negative correlation between
accounts receivable period and the three measures of profitability. In line with the
research hypothesis and the findings made by Padachi (2006), the correlation matrix in
Table 2 above produced significant negative correlation of accounts receivable period
53
with return on assets, return on equity and operating profit margin at the 1 percent
level. From the above table, the correlation coefficients of accounts receivable period
with return on assets, return on equity and operating profit margin are -38.08 percent, 67.28 percent and -61.85 percent respectively and they also indicate strong association
between accounts receivable period and profitability of firms. It can be interpreted as
longer accounts receivable period is associated with lower profitability and vice versa.
As it can be vividly seen in Table 4.2 there is statistical evidence that firm size is
significantly and positively correlated with return on assets, return on equity and
operating profit margin at the 1 percent, 5 percent and 10 percent levels with correlation
coefficients of 39.96 percent, 32.78 percent, and 22.84 percent respectively. Similarly,
financial leverage has significant negative correlations with return on assets and
operating profit margin at the 5 percent and 1 percent levels respectively. However, no
significant correlation is found between firm growth rate and the three profitability
measures.
In the same manner, another correlation analysis has been done to investigate the
relationship of profitability variables with inventory holding period, accounts payable
period, cash conversion cycle and current assets to total assets ratio. If efficient working
capital assets management increases profitability, one should expect negative
relationship between the measures of profitability and working capital assets
management variables.
Below, Table 4.3 presents the correlation results, along with the P-values in parenthesis,
for the three dependent profitability variables, return on assets, return on equity and
operating profit margin, with inventory holding period, accounts payable period, cash
conversion cycle and current assets to total assets ratio.
As it has been put in chapter three of this paper, the second research hypothesis expects
that there will be significant negative relationship between profitability measures and
inventory holding period. In agreement with this hypothesis, the correlation matrix in
54
Table 3 reveals that inventory holding period is significantly and negatively correlated
with return on assets, return on equity and operating profit margin at the 1 percent
level. The correlation coefficients, -38.70 percent with return on assets, -61.57 percent
with return on equity and -53.82 percent with operating profit margin, are all indicators
of strong negative relationship between inventory holding period and profitability.
Table 4.3: Correlation Analysis of Profitability Measures with Inventory Holding
Period, Accounts Payable Period, Cash Conversion Cycle and Current Assets to
Total Assets Ratio
ROA
ROE
OPM
IHP
ROA
1.0000
ROE
1.0000
0.8207
(0.0000)
OPM
0.7875
0.8813
1.0000
(0.0000) (0.0000)
IHP
-0.3870 -0.6157 -0.5382 1.0000
(0.0035) (0.0000) (0.0000)
APP
-0.1231 -0.0595 -0.2973 0.0677
(0.3704) (0.6664) (0.0275) (0.6234)
CCC
-0.3564 -0.6246 -0.4862 0.9462
(0.0076) (0.0000) (0.0002) (0.0000)
CATAR 0.2403
0.3102
0.3668
-0.0436
(0.0772) (0.0212) (0.0059) (0.7522)
Source: STATA correlation results based on annual
APP
CCC
CATAR
1.0000
-0.2142 1.0000
(0.1164)
-0.1305 -0.0381 1.0000
(0.3422) (0.7823)
reports of sample firms for the
study period
Similarly, it was hypothesized that there will be significant positive relationship
between accounts payable period and profitability as measured by return on assets,
return on equity and operating profit margin. Contrary to the research hypothesis, the
correlation matrix in Table 4.3 above produced negative relationship between accounts
payable period and profitability measures. However, these relations are not statistically
significant except for return on equity, the result for which statistical significance at the
5 percent level was observed.
55
Moreover, the correlation coefficients of -12.31 percent with return on assets, -5.95
percent with return on equity and -29.73 with operating profit margin shows relatively
weak relationship between the accounts payable period and firms’ profitability. The
negative relationship between accounts payable period and profitability goes with the
view that less profitable firms wait longer to pay their bills.
In this situation,
profitability may affect the accounts payable period and vice versa (Deloof, 2003; Falope
and Ajilore, 2009; Raheman and Nasr, 2007).
In the same manner, the hypothesis that there is significant negative relationship
between the cash conversion cycle (one of the comprehensive measures of working
capital assets management policies) and profitability of firms was tested. Accordingly,
the result of the correlation matrix in Table 4.3 above indicates that the cash conversion
cycle is significantly and negatively correlated with return on assets, return on equity
and operating profit margin at the 1 percent level. This strong relationship is also
evidenced from the correlation coefficients of 35.64 percent, 62.46 percent and 48.62
percent with return on assets, return on equity and operating profit margin respectively.
This finding is inline with finding made by Jose, et al. (1996), Sen and Oruc (2009), and
Falope and Ajilore (2009).
The other hypothesis that was stated in chapter three is that there is significant negative
relationship between the current assets to total assets ratio (the second comprehensive
measure of working capital assets management/investment policy) and the profitability
variables. Contrary to the hypothesis, however, the last row of the correlation matrix of
Table 4.3 indicate positive and significant correlation of current assets to total assets
ratio with return on assets, return on equity and operating profit margin at the 10
percent, 5 percent, and 1 percent levels respectively. The correlation coefficients, 24.03
percent for return on assets, 31.02 percent for return on equity and 36.68 percent for
operating profit margin, also indicate comparatively strong positive correlation between
the current assets to total assets ratio and firms’ profitability.
56
This finding is similar with the findings of Afza and Nazir (2007) and implies that there
is negative relationship between aggressiveness in working capital investment policy
and firms’ profitability.
As current assets to total assets ratio increases, degree of
aggressiveness in working capital investment policy decreases (working capital
investment is considered to be aggressive when investment in current asses is low) and
profitability of firms increases. (Discussion of the justifications is left for the regression
part)
The third correlation analysis has been carried out following the same approach in order
to look into the likely relationship of profitability variables with current liabilities to
total assets ratio (the explanatory variable used as proxy of working capital financing
efficiency) and the two conventional measures of liquidity, current ratio and quick ratio.
If efficient working capital financing policy increases profitability, one should expect
negative relationship between the measures of profitability and working capital
financing policy i.e. Return on assets, return on equity and operating profit margin on
one hand and current liabilities to total assets ratio on the other hand.
In finance literature, there is a trade off between profitability and liquidity, so we should
expect negative correlation between profitability measures and the two traditional
liquidity measures. Below, Table 4.4 reports the correlation results, along with the Pvalues in parenthesis, for the three dependent profitability variables, return on assets,
return on equity and operating profit margin, with current liabilities to total assets ratio,
current ratio and quick ratio.
The hypothesis that was stated in chapter three related to working capital financing
policy was that there is significant positive relationship between the current liability to
total assets ratio and the profitability variables. In agreement to the hypothesis, Table 4.4
below exhibits the result that indicates there is statistical evidence that the profitability
measures are positively related to the working capital financing efficiency.
57
However for operating profit margin, even though current liabilities to total assets ratio
is positively correlated, the statistical evidence is not significant. For the remaining two
measures of profitability, return on assets and return on equity, the correlation with
current liabilities to total assets ratio is statistically significant at the 1 percent and 5
percent level respectively.
Table 4.4: Correlation Analysis of Profitability Measures with Current Liabilities
to Total Assets Ratio, Current Ratio, Quick Ratio and GDP
ROA
ROE
OPM
CLTTAR
CR
QR
GDP
1.0000
0.8207
1.0000
(0.0000)
OPM
0.7875
0.8813
1.0000
(0.0000) (0.0000)
CLTAR
0.3877
0.2967
0.1991
1.0000
(0.0035) (0.0278) (0.1451)
CR
-0.2592
-0.1295
-0.0820
-0.3362
1.0000
(0.0560) (0.3462) (0.5519) (0.0121)
QR
-0.3297
-0.1904
-0.1623
-0.3999
0.9706
1.0000
(0.0140) (0.1639) (0.2364) (0.0025) (0.0000)
GDP
0.0565
0.0519
0.0536
0.0500
1.0000
0.0331
0.0135
(0.8105) (0.9222) (0.6822) (0.7069) (0.6977) (0.7171)
Source: STATA correlation results based on annual reports of sample firms for the
ROA
ROE
study period
The correlation coefficients for return on assets, return on equity and operating profit
margin are 38.77 percent, 29.67 percent and 19.91 percent respectively. This implies that
there is positive relationship between degree of aggressiveness in working capital
financing policy and firms’ profitability. The higher the current liabilities to total assets
ratio, the higher is the degree of aggressiveness in working capital financing policy, and
the higher will be the profitability. The firm is said to be aggressive in working capital
policy when it used large amounts of current liabilities to finance its working capital
requirements.
58
If efficiency in managing working capital investment and financing policies is related
only to profitability, the issue could have been easy. However, the issue at hand is also
highly related to the concept of liquidity which is quite opposite to the requirements for
profitability. Put it simply, the long term success of firms, in fact, is measured by their
profitability. On the other hand, their short term survival, which is the base for long
term success, depends on the availability of liquid assets to meet financial obligations on
time when they are due. Therefore, in finance theories there is a trade off between
profitability and liquidity. In line with this theoretical framework, it was hypothesized
that there is significant negative relationship (trade-off) between profitability measures
and the traditional measures of liquidity.
The correlation matrix in Table 4.4 shows the absence of significant relationship between
current ratio and the measures of profitability, except for return on assets for which the
result is significant at the 10 percent level. Similarly, the relationship between quick
ratio and profitability measures is insignificant, except for return on assets having a
result which is again significant at the 5 percent level. However, the correlation
coefficients show negative relationship between liquidity, as measured by both current
ratio and quick ratio, and the profitability measures. As indicated in the above table the
correlation coefficients for current ratio with return on assets, return on equity and
operating profit margin are -25.92 percent, -12.95 percent and -8.2 percent respectively.
Likewise, the correlation coefficients for quick ratio with return on assets, return on
equity and operating profit margin are -32.97 percent, -19.04 percent and -16.23 percent
respectively. Finally, GDP has no significant relationship with profitability measures.
To sum up the discussion on the correlation analysis, although the pair wise correlations
give proof of relationship between two variables; these measures do not allow us to
identify causes and effect relationships between such variables. From the results of
correlation analysis, it is difficult to say whether a shorter accounts receivable period
leads to higher profitability or shorter accounts receivable period is a result of the higher
profitability. In the same way, it is impossible to interpret the negative relationship
59
between inventory holding period and profitability variables by stating that a higher
profit is the result of shorter inventory holding period and vice versa. Simply the
correlation result shows the coefficient and the direction of relationship between two
variables with the level of significance. Another shortcoming of correlation analysis is
that it does not provide reliable indicators or coefficients of association in a manner
which control for additional explanatory variables. This means care must be exercised
when interpreting the pair wise correlation coefficients. In examining effect of some
variables on the other variables, the main analysis will be derived from
econometrics/regression analysis that overcomes the problems of correlation analysis.
4.4. Econometrics Analysis: Effect of Working Capital Policies on Firms’
Profitability
So far we established a framework of literature and data analysis including descriptive
statistics and correlation analysis in order to investigate the relationship between
working capital assets management/investment and financing policies and profitability.
In order to shed more light on the relationship between working capital management
and firms’ profitability and to further investigate the impact of management of working
capital investment and financing policies on firms’ profitability (in order to answer the
research questions in this study properly) eighteen (18) pooled linear panel data
(analysis of cross sectional and time series data) regression models have been run.
Moreover, six (6) additional regressions have been run in order to examine the
relationship between firms’ profitability and the traditional measures of liquidity. This
section of the study presents the results and discussions of the regression/econometrics
analysis.
Before running the regressions, the data sets have been tested for normality, outliers
(Observations that are very extreme compared to other observations that may cause
problems in estimating the regression coefficients), leverage (an observation with an
extreme value on a predictor variable) and influence (an observation is said to be
60
influential if removing the observation substantially changes the estimate of coefficients)
and some correction actions have been taken. Accounts receivable period and financial
leverage were skewed to the right and were transformed into their square roots to
correct non-normality of the variables. Similarly firm growth rate was skewed to the
right and transformed into its inverse to correct the non-normality of the variable. GDP
was also transformed into its inverse value to validate the normality assumption.
4.4.1 Accounts Receivable Period and Profitability
Three regressions were run to investigate the effect of accounts receivable period on
firms’ profitability. After running the three models, the results were tested for the
Classical linear regression model (CLRM) assumptions (See appendix C-1). Models with
Return on equity and operating profit margin as dependent variables were having
heteroscedasticity problem. Robust standard error was used to minimize the problem of
heteroscedasticity. However, tests for autocorrelations were not made since data
analysis technique was pooled cross sectional analysis thus mitigating the
autocorrelation problem by ignoring the time effect.
Table 4.5, below, illustrates the summary of the three regression models that have been
run to investigate the effect of accounts receivable period on firms’ profitability. The
explanatory power of the three models, as can be seen on Table 4.5 from the R squared
values are equal to 43.48 percent (adjusted), 61.35 percent and 59.54 percent for return
on assets, return on equity and operating profit margin respectively. This implies that
43.48 percent of the changes in the return on assets, 61.35 percent of variability in the
return on equity and 59.54 percent of changes in operating profit margin are
successfully explained by the variables used in the models. However, the remaining
56.52 percent changes in the return on assets, 38.65 percent variability in the return on
equity and 40.46 percent of changes in the operating profits are caused by other factors
that are not included in the models. Moreover, the overall significance of the models,
61
when measured by their respective F statistics of 9.31, 15.00 and 17.31 with P-values of
0.0000, indicate that the models are well fitted at 1 percent level of significance.
Table 4.5: Regression Analysis of Profitability Measures and Accounts Receivable
Period
ROA
ROE
OPM
Coef.
t-value
Coef.
t-value
Coef.
t-value
(Std.Err.) (p-value) (Std.Err.) (p-value) (Std.Err.) (p-value)
ARPsqrt -.122347
-4.19***
-.2404972
-6.11***
-.0358454
-3.56***
(.0292067)
(0.000)
(.00663)
(0.000)
(.0100699)
(0.001)
FS
.0419997
4.84***
.0817736
5.33***
.0752128
4.02***
(.0086808)
(0.000)
(.0153526)
(0.000)
(.0186922)
(0.000)
FGRinv
-.0013519
-1.75*
-.003226
-2.44**
-.0033623
-2.87***
(.0007737)
(0.087)
(.0013233)
(0.018)
(.0011724)
(0.006)
FLsqrt
-.111591
-2.07**
-.1674931
-0.94
-.4494253
-2.76***
(.0538784)
(0.044)
(.1774134)
(0.350)
(.1630243)
(0.008)
GDPinv
.3440713
0.20
2.420281
0.71
.2331876
0.07
(1.730205)
(0.843)
(3.405698)
(0.481)
(3.239536)
(0.943)
Number
55
55
55
of obs
F(5, 49)
9.31*** (P=0.0000)
15.00*** (P=0.0000)
17.31*** (P=0.0000)
R0.4871
0.6135
0.5954
squared
AdjR0.4348
squared
Root
0.12418
0.24413
0.26942
MSE
*** Significant at the 1 percent Level
** Significant at the 5 percent Level
* Significant at the 10 percent Level
Source: STATA regression results based on annual reports of sample firms for the
study period
In addition, Table 4.5 reveals the result of the regressions analysis in which accounts
receivable period (in its square root value) and firm size are both statistically significant
at the 1 percent level in all the three regressions. Firm growth rate (in its inverse value)
affects return on assets, return on equity and operating profit margin negatively and
significantly at the 10 percent, 5 percent and 1 percent levels respectively.
62
Similarly, financial leverage, in its square root value, affect return on assets and
operating profit margin negatively and significantly at the 5 percent and 1 percent levels
respectively, but it has no significant effect on the return on equity. While, GDP does not
have significant relationship with profitability measures used in this study.
Bearing in mind the third chapter of the report, the first research hypothesis was that
there is significant negative relationship between profitability measures and accounts
receivable period. In conformity with the hypothesis, all the three indicators of
profitability, return on assets, return on equity, and operating profit margin, are
negatively and significantly related with accounts receivable period at the 1 percent
level and these results are consistent with the findings made by Folope and Ajilore
(2009), Mathuva (2009), Padachi (2006), Samiloglu and Demirgunes (2008) and Sen and
Oruc (2009) who found significant negative relationship between accounts receivable
period and firms’ profitability.
The implication is that the increase or decrease in accounts receivable will significantly
and negatively affect profitability of the firms. It means that the shorter the firm’s
accounts receivable period, the higher will be the profitability and vice versa. This is
may be due to two reasons. One, if a firm collects its accounts receivable quickly the
fund will be available for productive usage. In this sense, the negative relationship
between accounts receivable period and firms’ profitability is consistent with the view
that the lesser the time it takes customers to pay their bills, results more cash available to
replenish the inventory. This in tern leads to more sales which ultimately results in an
increase in profitability. Two, it is also possible to minimize loss from uncollectable
accounts by speeding up the receivable period.
4.4.2 Inventory Holding Period and Profitability
In a similar fashion, three regressions were run in order to examine the effect of
inventory holding period on the three measures of profitability-return on assets, return
on equity and operating profit margin. While making tests for the Classical linear
63
regression model (CLRM) assumptions, the problems of heteroscedasticity and
normality were found (See appendix C-2). Robust standard error was used to minimize
the problem of heteroscedasticity and inventory holding period, the main independent
variable, was transformed into its square root value to correct the problem of normality.
Table 4.6: Regression Analysis of Profitability Measures and Inventory Holding
Period
IHPsqrt
FS
FGRinv
FLsqrt
GDPinv
Number
of obs
F(5, 49)
Rsquared
Adj Rsquared
Root
MSE
ROA
Coef.
t-value
(Std. Err.) (p-value)
-.0061802
-3.69***
(.0016738)
(0.001)
.035144
3.92***
(.0089613)
(0.000)
-.0008997
-1.74*
(.0005172)
(0.088)
-.1106097
-1.67
(.0663499)
(0.102)
-.3937911
-0.24
(1.613907)
(0.808)
55
ROE
Coef.
t-value
(Std. Err.) (p-value)
-.0205429
-3.61***
(.0056947)
(0.001)
.0590075
2.98***
(.0198291)
(0.005)
-.0017246
-1.21
(.0014301)
(0.234)
-.1638124
-0.89
(.1839651)
(0.378)
-.0215481
-0.01
(3.592665)
(0.995)
55
OPM
Coef.
t-value
(Std. Err.) (p-value)
-.0158092
-2.09**
(.0075589)
(0.042)
.0570857
2.38**
(.0239497)
(0.021)
-.0021598
-1.62
(.0013363)
(0.112)
-.4580804
-2.69***
(.1701976)
(0.010)
-1.942466
-0.55
(3.532805)
(0.585)
55
6.92*** (P=0.0001)
0.4185
6.30*** (P=0.0001)
0.4691
13.05*** (P=0.0000)
0.4574
-
-
-
0.13222
0.28613
0.312
*** Significant at the 1 percent Level
** Significant at the 5 percent Level
* Significant at the 10 percent Level
Source: STATA regression results based on annual reports of sample firms for the
study period
64
However, tests for autocorrelations were not made since data analysis technique was
pooled cross sectional analysis and thus mitigating the autocorrelation problem by
ignoring the time effect.
Above, Table 4.6 shows the results of regression models in which the impact of
inventory holding period on the three profitability measures ( return on assets, return
on equity and operating profit margin) have been examined. The explanatory power of
the three models, as can be seen on Table 4.6 from the R squared values, are 41.85
percent, 46.91 percent and 45.74 percent respectively. This is an indication that the
variables used in the models explain 41.85 percent of the changes in the return on assets,
46.91 percent of variability in the return on equity and 45.74 percent of changes in
operating profit margin.
Similar to the explanations given in previous paragraphs, the remaining percentages
reflect the portion which is not explained by the variables included in the models.
Moreover, the overall significances of the models when measured by their respective F
statistics of 6.92, 6.30 and 13.05 with P-values of 0.0001, 0.0001 and 0.0000 respectively
indicate that the models are well fitted at the 1 percent level of significance.
Furthermore, Table 4.6 presents the result of the regressions analysis in which inventory
holding period (in its square root value) and firm size are both statistically significant at
the 1 percent level in all the three regressions. In these models, firm growth rate (in its
inverse value) affects only return on assets negatively and significantly at the 10 percent
level. Similarly, financial leverage, in its square root value, showed a strong negative
relationship with operating profit margin at the 1 percent level, but it has no significant
relationships with return on assets and return on equity. While, in these regressions
also, GDP has no any significant relationship with profitability measures used in this
study.
The result from this study is inline with the initial hypothesis which states that there is
significant negative relationship between inventory holding period and profitability of
65
firms. This means that inventory holding period affects firms’ profitability, as measured
by return on assets, return on equity and operating profit margin, negatively and
significantly at the 1 percent, 1 percent and 5 percent levels respectively and this result
is conforms to findings of Folope and Ajilore (2009), Padachi (2006), Samiloglu and
Demirgunes (2008). The implication is that the increase or decrease in inventory holding
period will significantly and negatively affect profitability of the firms. In simple terms,
the shorter the firm’s inventory holding period, the higher will be the profitability and
vice versa. It can be also interpreted as if the inventory takes more time to sell, it will
adversely affect profitability. The reason for this could be tied up of more funds and/or
deterioration and obsolescence of inventory due to longer inventory period leads to
lower profitability.
4.4.3 Accounts Payable Period and Profitability
In a similar way, three regression models were run in order to examine the effect of
accounts payable period on the three measures of profitability-return on assets, return
on equity and operating profit margin. Heteroscedasticity problem was found while
testing the assumptions of the Classical Linear Regression Model (CLRM) (See
Appendix C-3).
Robust standard errors were used so as to mitigate the heteroscedasticity problem
witnessed in the process of testing the three regression outputs. However, tests for
autocorrelations were not made since data analysis technique was pooled cross sectional
analysis and thus mitigating the autocorrelation problem by ignoring the time effect.
Below, Table 4.7 presents the results of regression models in which the impact of
accounts payable period on the three profitability measures, return on assets, return on
equity and operating profit margin, has been examined. The explanatory power of the
three models, as can be vividly seen on Table 4.7 from the R squared values, are 30.86
percent for return on assets 22.26 percent for return on equity and 35.76 percent for
operating profit margin. This implies that 30.86 percent of the changes in the return on
66
assets, 22.26 percent of variability in the return on equity and 35.76 percent of changes in
operating profit margin are successfully explained by the variables used in the models.
However, the remaining 69.14 percent changes in the return on assets, 77.74 percent
variability in the return on equity and 64.24 percent of changes in the operating profits
are caused by other factors that are not included in the models.
Table 4.7: Regression Analysis of Profitability Measures and Accounts Payable
Period
ROA
APPsqrt
FS
FGRinv
FLsqrt
GDPinv
Number
of obs
F(5, 49)
R-squared
Adj Rsquared
Root MSE
ROE
Coef.
t-value
(Std. Err.) (p-value)
-.0037108
-0.34
(.0108071)
(0.733)
.0833942
3.03***
(.0274939)
(0.045)
-.0027015
-1.82*
(.0014858)
(0.075)
-.2317322
-0.85
(.272558)
(0.399)
-.0969339
-0.02
(4.491132)
(0.983)
55
OPM
Coef.
t-value
(Std. Err.) (p-value)
-.0175474
-1.74*
(.0100719)
(0.088)
.1030606
4.54***
(.0227026)
(0.000)
-.0024503
-1.92*
(.0012792)
(0.061)
-.3711186
-1.67
(.2227243)
0.102
-1.808718
-0.49
(3.695348)
(0.627)
55
7.04*** (P=0.0000)
0.3086
-
5.31*** (P=0.0000)
0.2226
-
16.21*** (P=0.0000)
0.3576
-
0.14418
0.34626
0.3395
Coef.
(Std. Err.)
-.0031788
(.0049338)
.0463
(.0124358)
-.0011289
(.0005318)
-.1114977
(.0765491)
-.3895509
(1.795767)
55
t-value
(p-value)
-0.64
(0.522)
3.72***
(0.001)
-2.12**
(0.0389)
-1.46
(0.152)
-0.22
(0.829)
*** Significant at the 1 percent Level
** Significant at the 5 percent Level
* Significant at the 10 percent Level
Source: STATA regression results based on annual reports of sample firms for the
study period
Moreover, consistent with the above two sets of regression results, the overall
significance of the models when measured by their respective F statistics of 7.04, 5.31
67
and 16.21 with P-values of 0.0000 indicate that the models are well fitted at the 1 percent
level of significance.
When we compare the results of these regressions with the above two sets of results,
there are significant differences. The R squared value of 30.86 percent for return on
assets is by far smaller than the R squared results for return on assets in the accounts
receivable period and inventory holding period results of regressions. By the same
analysis, the R squared values of 22.26 percent for return on equity and 35.76 percent for
operating profit margin are smaller than that of the corresponding R squared values of
regressions for accounts receivable period and inventory holding period. This implies
that the explanatory power of the independent variable, accounts payable period, is
relatively weaker than that of the two variables. Put simply, variability in accounts
payable period does not explain the variability of profitability variables as strongly as
accounts receivable period and inventory holding period.
In addition to what has been discussed above, Table 4.7 presents the result of the
regressions analysis in which accounts payable period (in its square root value) has no
significant impact on firms’ profitability as measured by return on assets and return on
equity but it has significant impact on profitability when it is measured by the operating
profit margin at the 10 percent level. The positive effect of firm size on profitability
measures is statistically significant at the 1 percent level in all the three regressions,
which is consistence with the above two sets of regressions. In these models, firm
growth rate (in its inverse value) affects all the three measures of profitability, return on
assets, return on equity and operating profit margin, negatively and significantly at the
5 percent, 10 percent and 10 percent levels respectively. Finally, no significant
relationship is found between financial leverage as well as GDP and the three measures
of profitability.
The study has found that there is no positive significant relationship between accounts
payable and profitability of firms, which is against the initial hypothesis. It means that
68
virtually no significant relationship is obtained between the accounts payable period
and profitability of firms from the regression analysis, except for the significant negative
effect of accounts payable period on operating profit margin at the 10 percent level. The
result is basically consistent with the findings of Teruel and Solano (2005) who founds
insignificant relationship between accounts payable period and profitability.
The researcher accepts these results for three reasons. First, in the literature of working
capital, research findings indicated both negative and positive significant relationships
between accounts payable period and profitability of firms (Falope and Ajilore, 2009;
Lazaridis and Tryfonidis, 2006; Nobanee, 2009; Raheman and Nasr, 2007). A positive
significant relationship between accounts payable period and profitability can be
explained by the increased availability of funds caused by the delayed payment of
accounts payable. Such funds can thus be used for productive purposes that can
increase profitability. On the other hand, a negative significant relationship between
accounts payable period and profitability can be explained by the benefits of early
payment discounts. What if these two benefits off-set each other? There will be no
significant relationship between accounts payable period and profitability of firms.
Second, most of the firms included in this study import the raw materials from abroad
and make purchases on accounts in accordance with the credit policy of the suppliers
due to low bargaining power. In this case, there may be no significant relationship
between accounts payable period and profitability. Finally, after all it is not delaying
payment or making it fast that matters. What matters is for what purpose we use the
fund at hand i.e. if we make it idle we expect no additional profits from delaying
payments for accounts payable. On the other hand, if we use it for productive purpose
we can expect some additional profits. Therefore, there may not be a significant
relationship between accounts payable period and profitability of firms. On the other
hand, the negative significant effect of accounts payable period on the operating profit
margin is consistent with the view that speeding up payment to suppliers might
69
increase profitability of firms due to substantial discounts for quick payment (Falope
and Ajilore, 2009).
4.4.4. Cash Conversion Cycle and Profitability
In the same manner, three regressions were run in order to examine the effect of cash
conversion cycle, one of the comprehensive measures of working capital investment
policy, on the three measures of profitability-return on assets, return on equity and
operating profit margin. Cash conversion cycle is an additive function of accounts
receivable period, inventory holding period and accounts payable period. Tests were
done for the Classical linear regression model (CLRM) assumptions. While making
these tests, the heteroscedasticity problems were encountered and robust standard
errors was used to minimize these problems (See Appendix C-4).
However, tests for autocorrelations were not made since data analysis technique was
pooled cross sectional analysis and thus it mitigates the autocorrelation problem by
ignoring the time effect.
Table 4.8 reveals the results of regression models in which the impact of cash conversion
cycle on the three profitability measures, return on assets, return on equity and
operating profit margin, has been examined. The explanatory power of the three
models, as can be seen on Table 4.8 from the R squared values, are 36.35 percent, 51.82
percent and 50.06 percent respectively. From this it is possible to infer that 36.35 percent,
of the changes in the return on assets, 51.82 percent of variability in the return on equity
and 50.06 percent of changes in operating profit margin are successfully explained by
the variables used in the models.
However, a large part, 63.65 percent changes in the return on assets, the remaining 48.18
percent of variability in the return on equity and 49.94 percent of changes in the
operating profits are caused by other factors that are not included in the models.
Moreover, the overall significances of the models when measured by their respective F
70
statistics of 7.11, 9.70 and 11.44 with P-values of 0.0000 indicate that the models are well
fitted at 1 percent level of significance.
Table 4.8: Regression Analysis of Profitability Measures and Cash Conversion
Cycle
ROA
Coef.
(Std. Err.)
CCC
FS
FGRinv
FLsqrt
GDPinv
Number
of obs
F(5, 49)
Rsquared
Adj Rsquared
Root
MSE
-.0000751
(.000026)
.0350369
(.0093288)
-.0012657
(.0005411)
-.1321814
( .0715291)
-.3480056
( 1.681015)
55
ROE
t-value
(Pvalue)
-2.88***
(0.006)
3.76***
(0.000)
-2.34**
(0.023)
-1.85*
(0.071)
-0.21
(0.837)
Coef.
(Std. Err.)
OPM
t-value
(P-value)
-.0003779
(.0000788)
.0494587
(.0183126)
-.0030047
(.0014535)
.272631
3.579496)
-.2193717
(.1870148)
55
-4.80***
(0.000)
2.70***
(0.009)
-2.07**
(0.044)
0.08
(0.940)
-1.17
(0.246)
Coef.
(Std. Err.)
t-value
(P-value)
-.0003078
(.0001294)
.0485209
(.0224504)
-.0031532
(.0013117)
-.4987009
(.1767569)
-1.697286
(3.517731)
55
-2.38**
(0.021)
2.16**
(0.036)
-2.40**
(0.020)
-2.82***
(0.007)
-0.48
(0.632)
7.11*** (P=0.0000)
0.3635
9.70*** (P=0.0000)
0.5182
11.44*** (P=0.0000)
0.5006
-
-
-
0.13833
0.2726
0.29934
*** Significant at the 1 percent Level
** Significant at the 5 percent Level
* Significant at the 10 percent Level
Source: STATA regression results based on annual reports of sample firms for the
study period
Moreover, Table 4.8 presents the result of the regressions analysis in which cash
conversion cycle and firm size significantly influence return on assets and return on
equity both at the 1 percent level also affecting operating profit margin significantly at
71
the 5 percent level. In these models, firm growth rate (in its inverse value) affects all the
three measures of profitability negatively and significantly at the 5 percent level.
Similarly, financial leverage, in its square root value, showed a strong negative
relationship with return on assets and operating profit margin at the 10 percent and 1
percent levels respectively. These regressions also show no significant relationship
between GDP and profitability measures.
The result from this study is complements with the hypothesis which was forwarded at
the beginning which states that there is a significant negative relationship between cash
conversion cycle and profitability of firms. This means that cash conversion cycle affects
firms’ profitability negatively and significantly at the 1 percent level (for return on assets
and return on equity) and at the 5 percent level (for operating profit margin). This result
is consistent with some previous findings (Deloof, 2003; Falope and Ajilore, 2009; Jose, et
al., 1996; Raheman and Nasr, 2007; Shin and Soenen, 1998; Zariyawati, et al., 2009).
The implication is that the increase or decrease in cash conversion cycle will
significantly and negatively affect profitability of the firms. It means that the shorter the
firm’s cash conversion cycle, the higher will be the profitability and vice versa. As stated
earlier, cash conversion cycle is an additive function of accounts receivable period,
inventory holding period and accounts payable period; i.e. cash conversion cycle is
equal to accounts receivable period plus inventory holding period minus accounts
payable period. Managing cash conversion cycle efficiently, therefore, means efficient
management of these three items. By managing efficiently the accounts receivable
period, inventory holding period and accounts payable period (by making short
accounts receivable period and inventory holding period and/or making long accounts
payable period) managers can control the efficiency of cash conversion cycle and its
impact on profitability.
72
4.4.5. Current Assets to Total Assets Ratio and Profitability
The above four measurements of working capital assets management policy, namely
accounts receivable period, inventory holding period, accounts payable period and cash
conversion cycle, indicate how efficient are firms in managing their collection, inventory
and payment policies. Investment in working capital assets, however, is broader than
managing collection, inventory and payment policies. It also includes management of
cash and other short term assets. For this reason, we need to have another
comprehensive measurement of working capital investment policy. In this study, the
researcher used current assets to total assets ratio as an additional comprehensive
measure of working investment policy.
In order to examine the effect of current assets to total assets ratio on measures of
profitability-return on assets, return on equity and operating profit margin, three
regression models were run. Robust standard error was used to mitigate
heteroscedasticity problem witnessed when testing the three regressions outputs for the
Classical linear regression model (CLRM) assumptions (See appendix C-5). However,
like all the other regressions, tests for autocorrelations were not made since the data
analysis technique was pooled cross sectional analysis and thus mitigating the
autocorrelation problem by ignoring the time effect.
Table 4.9, below, exhibits the regressions results of the effect of current assets to total
assets ratio on firms’ profitability as measured by the return on assets, return on equity
and operating profit margin. The explanatory powers of the three regressions as
measured by the R squired values are 30.35 percent for return on assets, 23.76 percent
for return on equity and 34.19 percent for operating profit margin.
These R squared values show relatively lower explanatory powers of the regressions
particularly in the one in which the dependent variable is return on equity. In this case,
the independent variables explain the variability of the dependent variable only to the
extent of 23.76 percent. The remaining 76.24 percent of variability in return on equity is
73
caused by other factors that are not included in the regression. Similarly, the
explanatory variables are able to explain the variability in return on assets and operating
profit margin only to the extent of 30.35 percent and 34.19 percent respectively.
Table 4.9: Regression Analysis of Profitability Measures and Current Assets to
Total Assets Ratio
ROA
CATAR
FS
FGRinv
FLsqrt
GDPinv
Coef.
(Std. Err.)
.0089697
(.0980119)
.0407193
(.0108746)
-.001218
(.000516)
-.1444938
(.0758139)
-.448844
(1.7934)
55
t-value
(P-value)
-0.09
(0.927)
3.74***
(0.000)
-2.36**
(0.022)
-1.91*
(0.063)
-0.25
(0.803)
Number
of obs
F(5, 49)
6.20*** (P=0.0002)
R0.3035
squared
Adj Rsquared
Root
0.14471
MSE
*** Significant at the 1 percent Level
ROE
Coef.
t-value
(Std. Err.) (P-value)
.2819629
0.92
(.3065822)
(0.362)
.0668963
3.15***
(.0212242)
(0.003)
-.0031537
-1.96*
(.0016061)
(0.055)
-.1766515
-0.71
(.2503764)
(0.484)
.4142309
0.10
(4.295842)
(0.924)
55
OPM
Coef.
(Std. Err.)
.2453645
(.258425)
.062188
(.0202532)
-.0032933
(.0012675)
-.4588792
(.2106716)
-1.55079
(3.600351)
55
t-value
(P-value)
0.95
(0.347)
3.07***
(0.003)
-2.60**
(0.012)
-2.18**
(0.034)
-0.43
(0.669)
4.91*** (P=0.0010)
0.2376
12.58*** (P=0.0000)
0.3419
-
-
0.34289
0.34361
** Significant at the 5 percent Level
* Significant at the 10 percent Level
Source: STATA regression results based on annual reports of sample firms for the
study period
The remaining 69.65 percent variability in the return on assets and 65.81 percent of
variability in operating profit margin are caused by variables that are excluded from the
models. The overall significances of the three models, however, when measured by their
74
respective F statistics of 6.20, 4.91 and 12.58 with P-values of 0.0002, 0.0010 and 0.0000
indicate that the models are well fitted at the 1 percent level of significance.
The results of the regressions analysis, in which current assets to total assets ratio has
shown insignificant positive effect on profitability measures, has been presented in
Table 4.9. From the same table, on the other hand, it can be learned that firm size has
positive significant influence on return on assets, return on equity and operating profit
margin at the 1 percent level. Firm growth rate (in its inverse value) affects return on
assets, return on equity and operating profit margin negatively and significantly at the 5
percent, 10 percent and 5 percent levels respectively. Similarly, financial leverage, in its
square root value, showed a strong negative relationship with return on assets and
operating profit margin at the 10 percent and 5 percent levels respectively. In these
regressions as well, GDP has no significant relationship with profitability measures.
In chapter three, it was hypothesized that current assets to total assets ratio affects firms’
profitability negatively and significantly. The results from this study, however, show
positive relationship between current assets to total assets ratio and firms’ profitability
even though the relationship is not statistically significant. The result may be acceptable
because most of firms included in the study have not yet fully used their fixed
production capacities. This means that if they want to increase their profitability, they
have to increase their investment in current assets until they reach the cost indifference
point. Keeping fixed assets constant (even decreasing through depreciation) and
investing more on current assets will then result in increased current assets to total
assets ratio. So, it may not be surprising to see positive relationship between current
assets to total assets ratio and profitability.
In agreement with the findings by Afza and Nasir (2007), the positive coefficients of
current assets to total assets ratio indicates a negative effect of the degree of
aggressiveness of working capital investment policy on firms’ profitability. It means that
as current assets to total assets ratio increases, degree of aggressiveness decreases, and
75
hence firms’ profitability increases. Accordingly, aggressiveness in working capital
investment policy affects the profitability of Tigray manufacturing private limited
companies negatively.
4.4.6. Current Liabilities to Total Assets Ratio and Profitability
To this point, the regression analyses were related to working capital investment policy.
In examining the effect of management of working capital on firms’ profitability, it is
also equally important to see the effect of working capital financing policy. Working
capital financing policy is measured by the relative aggressiveness/conservativeness in
using current liabilities to finance working capital assets. In measuring the effect of
working capital financing policy current liabilities to total assets ratio is used.
In order to examine the effect of working capital financing policy, as measured by
current liabilities to total assets ratio, on the profitability measures (return on assets,
return on equity and operating profit margin) three regression models were run. Robust
standard errors were used to mitigate the heteroscedasticity problem witnessed when
testing the three regressions outputs for the Classical linear regression model (CLRM)
assumptions (See appendix C-6).
However, like all the other regressions, tests for
autocorrelations were not made since the data analysis technique was pooled cross
sectional analysis and thus it mitigates the autocorrelation problem by ignoring the time
effect.
Below, Table 4.10 gives an idea about the regression results of the effects of current
liabilities to total assets ratio on firms’ profitability. The explanatory powers of the three
regressions as measured by the R squared values are 44.88 percent for return on assets,
30.24 percent for return on equity and 39.34 percent for operating profit margin. This
implies that 44.88 percent, of the changes in the return on assets, 30.24 percent of
variability in the return on equity and 39.34 percent of changes in operating profit
margin are successfully explained by the variables used in the models. However, the
remaining 55.12 percent of changes in the return on assets, 69.76 percent of variability in
76
the return on equity and 60.66 percent of changes in the operating profits are caused by
other factors that are not included in the models. Moreover, the overall significance of
the models when measured by their respective F statistics of 10.77, 8.97 and 21.85 with
P-values of 0.0000 indicates that the models are well fitted at the 1 percent level of
significance.
Table 4.10: Regression Analysis of Profitability Measures and Current Liabilities to
Total Assets Ratio
ROA
CLTAR
FS
FGRinv
FLsqrt
GDPinv
Numbe
r of obs
F(5, 49)
Rsquared
Adj Rsquared
Root
MSE
Coef.
t-value
(Std. Err.) (P-value)
.3721595
3.34***
(.1115135)
(0.002)
.0342887
3.43***
(.0099854)
(0.001)
-.0004086
-0.89
(.0004578)
(0.377)
-.20777
-3.76***
(.0552216)
(0.000)
-.0949818
-0.07
(1.408725)
(0.947)
55
ROE
Coef.
(Std. Err.)
.6301734
(.2410324)
.0661515
(.0203305)
-.0014294
(.0013365)
-.3789055
(.1643432)
.4236779
(3.984892)
55
t-value
(P-value)
2.61**
(0.012)
3.25***
(0.002)
-1.07
(0.290)
-2.31***
(0.025)
0.11
(0.916)
OPM
Coef.
t-value
(Std. Err.) (P-value)
.5948474
2.82***
(.211135)
(0.007)
.0607752
3.54***
(.0171789)
(0.001)
-.0016904
-1.56
(.0010855)
(0.126)
-.6431404
-4.20***
(.1532235)
(0.000)
-1.500607
-0.47
(3.190837)
(0.640)
55
10.77*** (P=0.0000)
0.4488
8.97*** (P=0.0000)
0.3024
21.85*** (P=0.0000)
0.3934
-
-
-
0.12874
0.32799
0.32989
*** Significant at the 1 percent Level
** Significant at the 5 percent Level
* Significant at the 10 percent Level
Source: STATA regression results based on annual reports of sample firms for the
study period
77
Besides, Table 4.10 displays the results of the regressions analysis in which current
liabilities to total assets ratio influence return on assets, return on equity and operating
profit margin positively and significantly at the 1 percent, 5 percent and 1 percent levels
respectively. On the other hand, there is significant statistical evidence on the same table
that indicates firm size strongly and positively influences return on assets, return on
equity and operating profit margin at the 1 percent level.
In these models, financial leverage (in its square root value) affects return on assets,
return on equity and operating profit margin negatively and significantly at the 1
percent, 5 percent and 1 percent levels respectively. Firm growth rate and GDP do no
have significant relationship with profitability measures.
The result from this study is in line with what was hypothesized, which states that there
is a positive significant relationship between current liabilities to total assets ratio and
profitability of firms. This means that current liabilities to total assets ratio affect return
on assets, return on equity and operating profit margin positively and significantly at
the 1 percent level (for return on assets and operating profit margin) and at the 5 percent
level (for return on equity). In contrary with the findings by Afza and Nasir (2007), the
positive coefficients of current liabilities to total assets ratio in this study point out the
positive effect of aggressive working capital financing policy on firms’ profitability.
The implication is that the increase or decrease in current liabilities to total assets ratio
will significantly and positively affect profitability of the firms. The higher the amount
of current liabilities the firm uses to finance its working capital assets, the more
profitable the firm will be. This implies that there is strong positive relationship between
aggressiveness in working capital financing and firms’ profitability. Moreover, the
coefficients of the regressions shows that profitability variables are strongly related with
working capital financing policy (as measured by current liabilities to total assets ratio)
than working capital investment policy. This means that working capital financing
78
policy affects firms’ profitability strongly than working capital investment policy in
sampled Tigray Manufacturing Private Limited Companies.
4.5. Trade-Off between the Two Objectives of Working Capital
Management: Profitability and Liquidity
Finally, six regressions were run to examine the relationship between the two objectives
of working capital assets management and financing policies; liquidity and profitability.
Theoretically, there is a trade-off between these two objectives. This means that the
higher the liquidity position of the firm, the lower will be the profitability and vice
versa. Thus, these regressions were run to get empirical evidence from the sampled
firms as to weather the trade-off between profitability and liquidity exists or not. The
two conventional measures of liquidity, current ratio and quick ratio, are used for the
purpose of analysis.
4.5.1. Current Ratio and Profitability
Three regressions were run in order to examine the effect of current ratio on return on
assets, return on equity, and operating profit margin. Tests were done for the Classical
linear regression model (CLRM) assumptions. While making these tests the problem of
heteroscedasticity was found and robust standard error was used to minimize this
problem (See appendix C-7). However, like all the other regressions tests for
autocorrelations were not made since data analysis technique was pooled cross sectional
analysis and thus it mitigates the autocorrelation problem by ignoring the time effect.
Table 4.11, below, put on display the regressions results of the effect of current ratio on
firms’ profitability as measured by the return on assets, return on equity and operating
profit margin. The explanatory powers of the three regressions as measured by the R
squared values are 63.66 percent, 31.41 percent and 42.86 percent for return on assets,
return on equity and operating profit margin respectively.
79
Table 4.11: Regression Analysis of Profitability Measures and Current Ratio
ROA
CRlog
FS
FGRinv
FLsqrt
GDPinv
Numbe
r of obs
F(5, 49)
Rsquared
Adj Rsquared
Root
MSE
Coef.
t-value
(Std. Err.) (P-value)
-.0891275
-6.69***
(.0133319)
(0.000)
.0351598
4.24***
(.0082887)
(0.000)
-.0003613
-1.05
(.0003429)
(0.297)
-.2318271
-5.22***
(.0444307)
(0.000)
-.8880556
-0.68
(1.305696)
(0.5000)
55
ROE
Coef.
(Std. Err.)
-.1066065
(.0389875)
.0702385
(.0180701)
-.0017806
(.0016625)
-.3747938
(.2053318)
-.692009
(3.986608)
55
t-value
(P-value)
-2.73***
(0.009)
3.89***
(0.000)
-1.07
(0.289)
-1.83*
(0.074)
-0.17
(0.865)
OPM
Coef.
(Std. Err.)
-.1176235
(.0387017)
.0636314
(.0150778)
-.0018566
(.0013573)
-.6564576
(.1794662)
-2.640887
(3.08039)
t-value
(P-value)
-3.04***
(0.004)
4.22***
(0.000)
-1.37
(0.178)
-3.66***
(0.001)
-0.86
(0.395)
55
24.58*** (P=0.0000)
0.6366
11.45*** (P=0.0000)
0.3141
32.36*** (P=0.0000)
0.4284
-
-
-
0.10453
0.32523
0.32023
*** Significant at the 1 percent Level
** Significant at the 5 percent Level
* Significant at the 10 percent Level
Source: STATA regression results based on annual reports of sample firms for the
study period
These R squared values show relatively higher explanatory powers of the regressions.
Particularly in the case of return on assets the independent variables explain the
variability of the dependent variable to the extent of 63.66 percent. Only the remaining
36.34 percent of variability in return on assets is caused by other factors that are not
included in the regression. Similarly, the explanatory variables are able to explain the
variability in return on equity and operating profit margin to the extent of 31.41 percent
and 42.86 percent respectively. The remaining 68.59 percent variability in the return on
equity and 57.14 percent of variability in operating profit margin are the result of
80
variables that are excluded from the models. In addition, the overall significances of the
three models when measured by their respective F statistics of 24.58, 11.45 and 32.36
with P-values of 0.0000 indicate that the models are well fitted at the 1 percent level of
significance.
Besides, Table 4.11 summarizes the result of the regressions analysis in which current
ratio have significant negative effect on all profitability measures. On the other hand, the
above same table will help us to observe the positive significant influence that firm size
has on return on assets, return on equity and operating profit margin at the 1 percent
level. Similarly, financial leverage, in its square root value, showed a strong negative
relationship with return on assets, return on equity and operating profit margin at the 1
percent, 10 percent and 1 percent levels respectively. However, firm growth rate and
GDP have no significant relationship with profitability measures.
Current ratio was hypothesized to have significant negative effect on firms’ profitability.
In conformity with this hypothesis, all the three indicators of profitability (return on
assets, return on equity, and operating profit margin) are negatively and significantly
related with current ratio at the 1 percent level. This finding is similar with the findings
of Christopher and Kamalavalli (2009), Eljelly (2004), Raheman and Nasr (2007), Sen and
Oruc (2009) and Shin and Soenen (1998). The implication is that the increase or decrease
in current ratio will significantly and negatively affect profitability of the firms. In other
words, the lower the firm’s current ratio, the higher will be the profitability and vice
versa.
4.5.2. Quick Ratio and Profitability
The last three regressions were run in order to examine the effect of quick ratio on
return on assets, return on equity, and operating profit margin. Tests were done for the
Classical linear regression model (CLRM) assumptions. Robust standard errors were
basically used so as to minimize the problem of heteroscedasticity which was observed
while carrying out the tests (See appendix C-8). However, like all the other regressions,
81
tests for autocorrelations were not made since data analysis technique was pooled cross
sectional analysis and thus mitigating the autocorrelation problem by ignoring the time
effect.
Table 4.12: Regression Analysis of Profitability Measures and Quick Ratio
ROA
QRlog
FS
FGRinv
FLsqrt
GDPinv
ROE
OPM
55
Coef.
t-value
(Std. Err.) (P-value)
-.0572673
-2.03**
(.028252)
(0.048)
.0816118
4.32***
(.0188707)
(0.000)
-.0024782
-1.57
(.0015828)
(0.124)
-.3286874
-1.62
(.2030682)
(0.112)
-.520075
-0.12
(4.204165)
(0.902)
55
Coef.
t-value
(Std. Err.) (P-value)
-.0766366
-2.71***
(.0283134)
(0.009)
.0773756
5.97***
(.0129626)
(0.000)
-.0025464
-1.98*
(.0012881)
(0.054)
-.6200995
-3.49***
(.1774368)
(0.001)
-2.539196
-0.81
( 3.13894)
(0.422)
55
15.44*** (P=0.0000)
0.5441
9.03*** (P=0.0000)
0.2773
33.02*** (P=0.0000)
0.4175
-
-
-
0.11707
0.33385
0.32327
Coef.
(Std. Err.)
-.0523866
(.011586)
.0450691
(.0099291)
-.0009178
(.0003346)
-.198145
(.0502971)
-.773813
(1.548902)
Number
of obs
F(5, 49)
Rsquared
Adj Rsquared
Root
MSE
t-value
(P-value)
-4.52***
(0.000)
4.54***
(0.000)
-2.74***
(0.008)
-3.94***
(0.000)
-0.50
(0.620)
*** Significant at the 1 percent Level
** Significant at the 5 percent Level
* Significant at the 10 percent Level
Source: STATA regression results based on annual reports of sample firms for the
study period
Table 4.12, above, presents the regressions results of the effect of quick ratio on firms’
profitability as measured by the return on assets, return on equity and operating profit
margin. The explanatory powers of the three regressions as measured by the R squared
values are 54.41 percent for return on assets, 27.73 percent for return on equity and 41.75
82
percent for operating profit margin. These R squared values show relatively higher
explanatory powers of the regressions. This is mainly the case in relation to the return
on assets in which case the independent variables explain the variability of the
dependent variable to the extent of 54.41 percent. Only the remaining 45.59 percent of
variability in return on assets is caused by other factors that are not included in the
regressions.
Similarly, the explanatory variables are able to explain the variability in return on equity
and operating profit margin to the extent of 27.73 percent and 41.75 percent respectively.
This means, the remaining 72.27 percent of variability in the return on equity and 58.25
percent of variability in operating profit margin are as a result of variables that are
excluded from the models. The overall significances of the three models when measured
by their respective F statistics of 15.44, 9.03 and 33.02 with P-values of 0.0000 indicate
that the models are well fitted at the 1 percent level of significance.
Additionally, Table 4.11 provides the results of the regressions analysis in which quick
ratio has significant negative effect on all profitability measures. On the other hand, the
table reveals the positive significant influence that firm size has on return on assets,
return on equity and operating profit margin at the 1 percent level. Firm growth rate, in
its inverse value, affects negatively and significantly return on assets and operating
profit margin at the 1 percent and 10 percent levels respectively. Similarly, financial
leverage, in its square root value, showed a strong negative relationship with return on
assets and operating profit margin at the 1 percent, level. Like all the previous
regressions, it has been noticed that there is no significant relationship between GDP
and profitability measures.
Quick ratio was hypothesized to have significant negative effect on firms’ profitability.
In conformity with the hypothesis, all the three indicators of profitability (return on
assets, return on equity, and operating profit margin) are negatively and significantly
related with quick ratio at the 1 percent, 5 percent and 1 percent levels respectively and
83
this finding is also consistent with the findings of some of the previous researchers
(Christopher and Kamalavalli, 2009; Nobanee, 2009). The implication of this finding is
that the increase or decrease in quick ratio will significantly and negatively affect
profitability of the firms. This means that the lower the firm’s quick ratio, the higher will
be the profitability and vice versa. Thus, quick ratio affects firms’ profitability negatively
and significantly and it is possible to increase profitability of Manufacturing Private
Limited Companies in Tigray by keeping quick ratio lower to the optimal level.
Finally, from the last two sets of regressions, we can learn that profitability and liquidity
(as measured by both current ratio and quick ratio) are related inversely among
Manufacturing Private Limited Companies operating in the Tigray region. This means is
that as liquidity of firms increases, profitability will be decreases and vice versa. This
finding is basically complement with the findings made by Elljelly (2004), Raheman and
Nasr (2007) and Sen and Oruc (2009). From this finding we can infer that there is a
trade-off between the two objectives of working capital management- liquidity and
profitability, in Tigray Manufacturing Private Limited Companies. This implies that
these companies can earn a better return by decreasing their liquidity position to a
reasonable minimum level.
84
CHAPTER V
CONCLUSION AND RECOMMENDATIONS
While working capital assets and the related short-term liabilities affect the firms’
profitability, liquidity (risk) as well as market values of shares (Smith, 1980). Research
studies on the effects of management of working capital policies on firms’ profitability
in developing countries, especially in Ethiopia remained an ignored area of empirical
research. To the best of researcher’s knowledge, no research has been done on the effects
of management of working capital policies on firms’ profitability in Ethiopia in general
and in Tigray in particular. Thus, this study examined the effect of working capital
investment and financing policies on firms’ profitability by using audited financial
statements of a sample of 11 manufacturing private limited companies in Tigray region,
Ethiopia for the period of 2005 to 2009.
The study used return on assets, return on equity and operating profit margin as
dependent profitability variables. Accounts receivable period, inventory holding period
and accounts payable period were used as independent working capital investment
policy variables. Moreover, cash conversion cycle and current assets to total assets ratio
were used as comprehensive measures of working capital investment policy. On the
other hand, current liabilities to total assets ratio is used as measure of working capital
financing policy. The two traditional measures, current ratio and quick ratio, were used
as liquidity indicators. In addition, the study used firm size as measured by logarithm of
sales, firm growth rate as measured by the change in annual sales, financial leverage
and annual GDP growth rate as control variables.
Descriptive statistics were used to examine the trend of the chosen variables among the
sampled firms.
Both correlation analysis and pooled panel data regression models of
cross-sectional and time series data were used to analyze the relationships among
working capital investment and financing policies’ variables and profitability variables.
85
The profitability positions of the 11 companies included in this study, as measured by
return on assets, return on equity and operating profit margin, are on average 5.22
percent, 1.19 percent and -5.73 percent respectively. Whilst, their liquidity positions, as
measured by the current and quick ratios, are on average 5.34 and 2.97 respectively.
Similarly, the average accounts receivable period, inventory holding period and
accounts payable period are 120 days, 314 days and 120 days respectively. On the other
hand, cash conversion cycle and current assets to total assets ratio, the two
comprehensive measures of working capital investment policy, are on average 314 days
and 48.10 percent respectively. Current liability to total assets ratio, used as measure of
working capital financing policy, is 24.41 percent on average among the manufacturing
private limited companies of Tigray. On average the size of manufacturing private
limited company in Tigray is Br. 20,378,683.78 in terms of annual sales with growth rate
of 115.31 percent, even if there is a higher variation in growth rate of individual sampled
firms. The financial leverage of the sampled firms, as measured by total liabilities to
total assets ratio, is 71.77 percent on average.
Findings of correlation analysis reveals that there exist strong negative relationships
between profitability measures and account receivable period, inventory holding period
and cash conversion cycle at the 1 percent level. Similarly, the correlation analysis
shows that accounts payable period is negatively related to the three measures of
profitability but this relationship is not statistically significant.
On the other hand, current assets to total assets ratio shows strong positive relationship
with return on assets, return on equity and operating profit margin at the 10 percent, 5
percent and 1 percent levels respectively. This finding is similar with the findings of
Afza and Nazir (2007). This finding implies that there is negative relationship between
aggressiveness in working capital investment policy and firms’ profitability. As current
assets to total assets ratio increases, the degree of aggressiveness in working capital
investment policy decreases (working capital investment is considered to be aggressive
when investment in current asses is low) and profitability of firms increases.
86
Similarly, the correlation analysis indicates strong positive relationship between current
liabilities to total assets ratio and profitability measures. By the same interpretation,
there is positive relationship between degree of aggressiveness in working capital
financing policy and firms’ profitability. A firm is said to be aggressive in working
capital financing policy when it uses large amounts of current liabilities relative to total
sources of funds. The higher the current liabilities to total assets ratio, the higher is the
degree of aggressiveness in working capital financing policy, and so is the
corresponding level of profitability.
The correlation analysis also shows that the absence of significant relationship between
current ratio and the measures of profitability, except for return on assets, for which the
result is significant at the 10 percent level. Similarly, the relationship between quick
ratio and profitability measures is insignificant, except for return on assets for which the
result is significant at the 5 percent level. However, the correlation coefficients show
negative relationship between liquidity, as measured by both current ratio and quick
ratio, and the profitability measures.
The regressions analyses reveal that, all the three indicators of profitability- return on
assets, return on equity and operating profit margin, are negatively and significantly
related to accounts receivable period at the 1 percent level. These results are consistent
with most of previous studies. The implication is that the increase or decrease in
accounts receivable period will significantly and negatively affect profitability of the
firms. This means that the shorter the firm’s accounts receivable period, the higher will
be their profitability and vice versa. Thus, this result communicates that managers can
increase the profitability of firms by reducing the accounts receivable period to the
possible minimum level. As one can see from the findings, the accounts receivable
period is relatively long for Tigray manufacturing private limited companies. The
researcher, therefore, recommends them to decrease their accounts receivable period to
a reasonable minimum level.
87
Likewise, from the findings of the regression analyses, inventory holding period
negatively and significantly affects firms’ profitability, as measured by return on assets,
return on equity and operating profit margin, at the 1 percent, 1 percent and 5 percent
levels respectively. This result is also consistent with most of previous studies. The
implication is that the increase or decrease in inventory holding period will significantly
and negatively affect profitability of the firms. This means that the shorter the firm’s
inventory holding period, the higher will be the profitability and vice versa. It can also
be interpreted as, if the inventory takes more time to sell, it will adversely affect
profitability. Therefore, it is possible to maximize the profitability of firms by speeding
the inventory turnover. The researcher recommends the finance managers of
manufacturing companies in Tigray to speedup the inventory turnover as much as
possible thereby to reduce the inventory holding period to a reasonable minimum level.
Accounts payable period shows a negative effect on the firms’ profitability. This result,
however, is not significant for return on assets and return on equity. The interpretation
for this can be profitability of Tigray manufacturing privet limited companies does not
depend upon accounts payable period. The significant negative relationship between
accounts payable period and operating profit margin is consistent with the view that
speeding up payments to suppliers might increase profitability of firms due to
substantial discounts for quick payment. In a condition where there is a higher discount
for early payments managers can maximize profitability by reducing the accounts
payable period. However, the amount of the discount should be large enough to cover
the opportunity cost of early payment and to make some profit.
The cash conversion cycle negatively and significantly affects firms’ profitability at the 1
percent level (for return on assets and return on equity) and at the 5 percent level (for
operating profit margin). These results are also consistent with some of previous
studies. The implication is that the increase or decrease in cash conversion cycle will
significantly and negatively affect profitability of the firms. It means that the shorter the
firm’s cash conversion cycle, the higher will be the profitability and vice versa. Thus,
88
Tigray manufacturing private limited companies can increases their profitability by
making their cash conversion cycle shorter to the optimal level. Thus, the researcher
recommends that Tigray manufacturing private limited companies should make their
cash conversion cycle short to the optimal level.
The results of the regression analyses also indicate that current liabilities to total assets
ratio positively and significantly influences return on assets, return on equity and
operating profit margin at the 1 percent, 5 percent and 1 percent levels respectively. The
implication is that the increase or decrease in current liabilities to total assets ratio will
significantly and positively affect profitability of the sampled firms. It means that the
higher the amount of current liabilities the firm uses to finance its working capital
assets, the more profitable it will be. This implies that there is strong positive
relationship between aggressiveness in working capital financing and the firms’
profitability.
Moreover, the coefficients of the regressions show that profitability variables are
strongly related with working capital financing policy, as measured by current liabilities
to total assets ratio, than working capital investment policy. It means that working
capital financing policy affects firms’ profitability strongly than working capital
investment policy. Tigray manufacturing firms, therefore, can increase profitability by
using more aggressive way of financing for their working capital requirements. Thus,
the researcher recommends that Tigray manufacturing private limited companies to use
more aggressive way of financing such as trade credit and short term bank loan for their
working capital requirements.
Finally, both measures of liquidity- current ratio and quick ratio, show significant
negative relationship between profitability and liquidity of Tigray manufacturing
private limited companies. This result is consistent with the view that there is a trade-off
between liquidity and profitability. Thus, Tigray manufacturing private limited firms
can increase profitability by reducing their liquidity position at least to the commonly
89
known level (2 for current ratio and 1 for quick ratio). Managers, therefore, can increase
firms’ profitability by improving the efficiency of management of working capital
investment and financing policies while, also keeping in view of the trade-off between
liquidity and profitability.
Further Research Directions
This study has highlighted a number of issues that warrant further research in order to
examine the effects of working capital policies on firms’ profitability. The three key
directions for this research are: increasing the scope of this study to include other
factors, using large sample size and using primary sources of data. Taking the previous
studies and the current work as a stepping stone, studies should be strengthen on the
effects of working capital policies on firms’ profitability to other economic sectors
(particularly in merchandising sector) in Ethiopia. Also as reliable findings results from
observations that are large enough to represent the study population and to study the
issue at hand by using the appropriate methodology, studies based on the use of long
time series data and increased number of observations (sample companies) are needed
to gain more insights into the issue at hand. Furthermore, it is equally vital to study the
effect of working capital policies on firms’ operating and financial risks while doing a
research on this topic. Moreover, it is also important to examine the difference in
working capital policies followed by different industries and determinants of working
capital policies for each industry. Finally, it is important to use primary source of data
particularly to provide company specific recommendations.
90
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